Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning | Paper Citation Record

Observation a5501b37-11b3-4f3f-9bdf-89d65010107c · outbound

This paper cites Learning to learn by gradient descent by gradient descent.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning to learn by gradient descent by gradient descent

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:45.971618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d486b4e4-e7eb-4846-adb5-9fac7b259e2b · outbound

This paper cites Multi-task feature learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Multi-task feature learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:45.981513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d3f9188-c2ac-4119-a774-704c8111ce9f · outbound

This paper cites Optimization with sparsity-inducing penalties.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Optimization with sparsity-inducing penalties

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:45.997939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0e8a0e6-dc8b-4703-8f6b-2118393c36c4 · outbound

This paper cites Meta-learning with adaptive hyperparameters.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta-learning with adaptive hyperparameters

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.007251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f500c83e-6517-4497-a847-791af7ae1049 · outbound

This paper cites Theoretical models of learning to learn.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Theoretical models of learning to learn

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.014768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 955d7226-facc-475b-a9cf-61a31b33c9d8 · outbound

This paper cites Meta learning via learned loss.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta learning via learned loss

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.023228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76f6c6e5-d761-4a38-a689-4456a27c035a · outbound

This paper cites Bengio, S.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Bengio, S

Reference 7

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T17:35:48.766357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0b1b94be-1077-4470-a906-1151169ada58 · outbound

This paper cites What is the state of neural network pruning? Proceedings of machine learning and systems, 2: 0 129--146, 2020.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning What is the state of neural network pruning? Proceedings of machine learning and systems, 2: 0 129--146, 2020

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.053508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38cc9345-abcc-4244-8522-b327252f1941 · outbound

This paper cites Evograd: Efficient gradient-based meta-learning and hyperparameter optimization.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Evograd: Efficient gradient-based meta-learning and hyperparameter optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.059775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0299793a-a5d0-46bb-9bba-e2491b09af16 · outbound

This paper cites Distributed optimization and statistical learning via the alternating direction method of multipliers.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Distributed optimization and statistical learning via the alternating direction method of multipliers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.070903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a123e2d8-da70-4ebf-ae96-6d36571df79c · outbound

This paper cites learning-compression.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning learning-compression

Reference 11

Resolution: verified exact; raw_fallback, observed 2026-08-10T17:35:48.672716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 128c7dbc-d6f2-46d6-a9d7-0b8efaf68a63 · outbound

This paper cites Multitask learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Multitask learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.085433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e6c1cef-04f7-470c-91bc-66e95cad81a6 · outbound

This paper cites A convex formulation for learning shared structures from multiple tasks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning A convex formulation for learning shared structures from multiple tasks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.092165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0735859-352e-4012-acf4-c4dc7398121a · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.098571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08ea65b5-ee92-4c51-b2c5-3846c1268c34 · outbound

This paper cites Metalr: Meta-tuning of learning rates for transfer learning in medical imaging.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Metalr: Meta-tuning of learning rates for transfer learning in medical imaging

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.106232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d957536-3ebd-49f2-bdb1-39cd03575933 · outbound

This paper cites Signal recovery by proximal forward-backward splitting.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Signal recovery by proximal forward-backward splitting

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.112001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 715e2960-90fb-4b40-821e-009d0cc46d34 · outbound

This paper cites Multi-Task Learning with Deep Neural Networks: A Survey.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Multi-Task Learning with Deep Neural Networks: A Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.120525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0374493a-2575-4fe4-87de-41aea308133c · outbound

This paper cites Structured Sparsity Inducing Adaptive Optimizers for Deep Learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Structured Sparsity Inducing Adaptive Optimizers for Deep Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.128312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf015dc3-3e89-406f-ae79-c3efc6c32188 · outbound

This paper cites Model compression and hardware acceleration for neural networks: A comprehensive survey.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Model compression and hardware acceleration for neural networks: A comprehensive survey

Reference 19

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T17:35:48.356903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 486df19c-f9a3-444e-9994-84207b81f30e · outbound

This paper cites In defense of parameter sharing for model-compression.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning In defense of parameter sharing for model-compression

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.155869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 313e0097-fb47-4a5f-a9c5-94426ccf93ef · outbound

This paper cites Sparse Networks from Scratch: Faster Training without Losing Performance.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Sparse Networks from Scratch: Faster Training without Losing Performance

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.162929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b689112-4639-464c-ab79-711d1fb7a76d · outbound

This paper cites Learning to learn by jointly optimizing neural architecture and weights.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning to learn by jointly optimizing neural architecture and weights

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.173320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d27601d-c64e-4100-aeba-59bedc9be097 · outbound

This paper cites Neural architecture search: A survey.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Neural architecture search: A survey

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.181986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51bedce8-bd43-4b1f-9db8-f176d0c6de22 · outbound

This paper cites Meta-learning of neural architectures for few-shot learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta-learning of neural architectures for few-shot learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.188252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bf25e6b-b28e-41cd-a32d-4c0a298d3587 · outbound

This paper cites Rigging the lottery: Making all tickets winners.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Rigging the lottery: Making all tickets winners

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.199005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6862044-44c8-4043-9992-f2dfed85ede5 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Model-agnostic meta-learning for fast adaptation of deep networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.206007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6a89aab-4752-4bd7-b084-6e82ab5173ed · outbound

This paper cites Bilevel programming for hyperparameter optimization and meta-learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Bilevel programming for hyperparameter optimization and meta-learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.214606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 063261ee-56fb-4261-9294-0987a9e81574 · outbound

This paper cites The lottery ticket hypothesis: Finding sparse, trainable neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning The lottery ticket hypothesis: Finding sparse, trainable neural networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.220727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddcde12d-6cfd-4def-975b-995732b15bdb · outbound

This paper cites The State of Sparsity in Deep Neural Networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning The State of Sparsity in Deep Neural Networks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.237458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd6e6939-b6ca-4e7a-b93e-157938e12e07 · outbound

This paper cites Searching for robustness: Loss learning for noisy classification tasks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Searching for robustness: Loss learning for noisy classification tasks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.248840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e51fcfe-df6d-4316-8917-56b6b481fa62 · outbound

This paper cites Meta Mirror Descent: Optimiser Learning for Fast Convergence.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta Mirror Descent: Optimiser Learning for Fast Convergence

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.255291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38fb3a02-b716-4d68-bce6-f5b5577f133a · outbound

This paper cites Loss function learning for domain generalization by implicit gradient.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Loss function learning for domain generalization by implicit gradient

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.966273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1f78339a-71d6-4311-9f61-6fd54f7d1efe · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Understanding the difficulty of training deep feedforward neural networks

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.942453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 96ee0780-707a-43de-807e-2fd1a9f961f0 · outbound

This paper cites Gon c alves, Fernando J.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Gon c alves, Fernando J

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.918102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 97015cf5-aec3-461d-9445-11edfb3bb461 · outbound

This paper cites Deep Learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Deep Learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.898760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e082c71d-fea7-4e8e-aeb3-7a3a84cdd868 · outbound

This paper cites Learning both weights and connections for efficient neural network.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning both weights and connections for efficient neural network

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.286331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e29d90b9-a5e5-41ba-bf5d-c8cfe45ea59e · outbound

This paper cites A closer look at learned optimization: Stability, robustness, and inductive biases.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning A closer look at learned optimization: Stability, robustness, and inductive biases

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.848896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e34c0b4-c4e2-46e1-a096-f892e64bd521 · outbound

This paper cites Statistical learning with sparsity: the lasso and generalizations.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Statistical learning with sparsity: the lasso and generalizations

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.299009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7e922c2-d122-4465-940e-326b748c4e67 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Distilling the Knowledge in a Neural Network

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.304526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82b19305-5016-43d6-8a2a-052f977c737c · outbound

This paper cites Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.796590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fe15ffd3-bca4-45b9-afb4-664e8c1c8ba5 · outbound

This paper cites Hospedales, A.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Hospedales, A

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.318977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04e8e200-7527-4044-9102-5fcfa5b4a3b2 · outbound

This paper cites Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Revisiting single image depth estimation: Toward higher resolution maps with accurate object boundaries

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.765355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8cea7d69-3c5c-47c1-a6d6-7322d17c4d74 · outbound

This paper cites Neural network pruning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Neural network pruning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.744479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 84edbc99-194c-4708-85e2-b2955c7e495b · outbound

This paper cites A survey of deep meta-learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning A survey of deep meta-learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.718702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 53bcd990-fb01-4ade-8adb-345773240117 · outbound

This paper cites Janowsky.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Janowsky

Reference 45

Resolution: verified exact; doi, observed 2026-08-10T17:35:47.148303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b11b92d5-979c-4570-9d8f-bdb773868c61 · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.691919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 313e9252-3ac5-4fc0-b208-01655e15f204 · outbound

This paper cites Learning task structure via sparsity grouped multitask learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning task structure via sparsity grouped multitask learning

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-10T17:35:48.058203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e804674-9fac-4df2-be2a-a69226b7b558 · outbound

This paper cites Soft threshold weight reparameterization for learnable sparsity.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Soft threshold weight reparameterization for learnable sparsity

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.672711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e532850-b7cf-4c80-9d7c-95541764bd70 · outbound

This paper cites Maskgan: Towards diverse and interactive facial image manipulation.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Maskgan: Towards diverse and interactive facial image manipulation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.651550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a225eea-6109-459c-b6ee-6df208c9a857 · outbound

This paper cites Layer-adaptive sparsity for the magnitude-based pruning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Layer-adaptive sparsity for the magnitude-based pruning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.625736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ce83794c-4505-46c0-a53a-f987f6f4552a · outbound

This paper cites Learning to Optimize Neural Nets.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning to Optimize Neural Nets

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.399009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce39489b-ce26-4a82-86ef-88e9ecbff95f · outbound

This paper cites Meta-SGD: Learning to Learn Quickly for Few-Shot Learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.404773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 516b0f6d-aacc-4373-9c17-154870620a61 · outbound

This paper cites Towards fast adaptation of neural architectures with meta learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Towards fast adaptation of neural architectures with meta learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.597845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9b51486e-fce1-4ed0-ae56-cf8f509dd7fd · outbound

This paper cites Auxiliary Tasks in Multi-task Learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Auxiliary Tasks in Multi-task Learning

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.418558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 175be6e5-34da-441f-8646-7ce2264d894e · outbound

This paper cites sparseland.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning sparseland

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.573763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 878019d0-5cec-4dd5-8d87-a3eb53b81443 · outbound

This paper cites Learning efficient convolutional networks through network slimming.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning efficient convolutional networks through network slimming

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.440752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c723d388-2245-4615-baec-5a4547645e30 · outbound

This paper cites Rethinking the Value of Network Pruning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Rethinking the Value of Network Pruning

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.449770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2cb1b7ec-a4cc-4efc-b44d-08b4c3361694 · outbound

This paper cites Learning gradient descent: Better generalization and longer horizons.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning gradient descent: Better generalization and longer horizons

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.529860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1836e164-72df-4bac-9aa9-71271fbd9f9f · outbound

This paper cites Pruning filter in filter.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Pruning filter in filter

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.496895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cd516bb9-96a0-47d6-9402-4d43cbb745bc · outbound

This paper cites Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.475611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b774d028-b852-4e02-966b-11a54953899f · outbound

This paper cites VeLO: Training Versatile Learned Optimizers by Scaling Up.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning VeLO: Training Versatile Learned Optimizers by Scaling Up

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.484497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1985698e-968d-416c-b56a-ba3301432489 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Indoor segmentation and support inference from rgbd images

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.494276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09a5c9b1-6460-4bde-a66b-1978e228310d · outbound

This paper cites On First-Order Meta-Learning Algorithms.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning On First-Order Meta-Learning Algorithms

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.513093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 068b1062-29e0-4c07-8f94-01ee729c5d40 · outbound

This paper cites Joint covariate selection and joint subspace selection for multiple classification problems.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Joint covariate selection and joint subspace selection for multiple classification problems

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.446782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c14e9650-5e8f-4fdf-a911-828e3853902d · outbound

This paper cites Proximal algorithms.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Proximal algorithms

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.531804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a82e38a8-e95f-44d3-9cab-cb944a53eb3f · outbound

This paper cites Senthil Kumar.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Senthil Kumar

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.550673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 259da896-6dd6-4f07-bb7b-0349d946b7d9 · outbound

This paper cites Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.565385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdd22e15-0d57-4cb8-9e96-99bf9709655b · outbound

This paper cites Learning symbolic model-agnostic loss functions via meta-learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning symbolic model-agnostic loss functions via meta-learning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.405153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c5c91938-3b79-4ed9-90e3-d1e02a45bae8 · outbound

This paper cites Online loss function learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Online loss function learning

Reference 70

Resolution: verified exact; raw_fallback, observed 2026-08-10T17:35:47.732752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation feed63eb-6fe1-4b66-88fa-504917e086c5 · outbound

This paper cites A comprehensive survey of neural architecture search: Challenges and solutions.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning A comprehensive survey of neural architecture search: Challenges and solutions

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.384336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb9ffae2-6cfc-489c-a769-4b0b822d83fb · outbound

This paper cites Across-task neural architecture search via meta learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Across-task neural architecture search via meta learning

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.352752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7b2128b9-f0a6-449f-8d0b-1db1e6feedd8 · outbound

This paper cites Low-rank matrix factorization for deep neural network training with high-dimensional output targets.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Low-rank matrix factorization for deep neural network training with high-dimensional output targets

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.833060Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f79635e-f6bc-4b2c-ba16-7dea9453fb2a · outbound

This paper cites Towards stochasticity of regularization in deep neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Towards stochasticity of regularization in deep neural networks

Reference 74

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T17:35:47.626376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fab8df72-841e-46b6-9f58-ad913bd1a84d · outbound

This paper cites Group sparse regularization for deep neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Group sparse regularization for deep neural networks

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.856764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0036e8d9-2abc-469f-9844-0fb4dcdc158a · outbound

This paper cites Evolutionary principles in self-referential learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Evolutionary principles in self-referential learning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.284399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3505617a-eb6f-4b36-aae8-9b3fcafe9529 · outbound

This paper cites Meta-learning sparse compression networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta-learning sparse compression networks

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.264983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a30661a-0142-4238-87be-e7ff40d79a01 · outbound

This paper cites Meta architecture search.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta architecture search

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.241465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4f3eee3a-9885-4e1b-8a39-9de13f1cb938 · outbound

This paper cites Learning a minimax optimizer: A pilot study.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning a minimax optimizer: A pilot study

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.220952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 311a3727-9a7a-4eb5-8462-a3007e598a01 · outbound

This paper cites LEARNED LEARNING RATE SCHEDULES FOR DEEP NEURAL NETWORK TRAINING USING REINFORCEMENT LEARNING , 2023.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning LEARNED LEARNING RATE SCHEDULES FOR DEEP NEURAL NETWORK TRAINING USING REINFORCEMENT LEARNING , 2023

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.194446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f85775fc-e675-4b1d-8dd6-a30e3a07a223 · outbound

This paper cites Learning sparse sharing architectures for multiple tasks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning sparse sharing architectures for multiple tasks

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.173406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4be01b0a-c06c-485e-89ff-d00f98461c11 · outbound

This paper cites Adashare: Learning what to share for efficient deep multi-task learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Adashare: Learning what to share for efficient deep multi-task learning

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.152239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cd6d2cc1-ba67-44aa-a62f-56cfde8538cb · outbound

This paper cites an unresolved cited work.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Unresolved cited work

Reference 83

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:35:49.130948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1e3ab091-cea5-491d-a5a1-df08120b278f · outbound

This paper cites Thrun and L.Y.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Thrun and L.Y

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.110810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9b4de533-0bb8-4d92-ace8-64e40595407e · outbound

This paper cites Learning to learn.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning to learn

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.930010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4c47114-0f68-4cbc-a96f-4e3b36c30e4f · outbound

This paper cites Meta-learning approaches for learning-to-learn in deep learning: A survey.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Meta-learning approaches for learning-to-learn in deep learning: A survey

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.074316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4123d499-20f5-4ab0-b340-db3cf3f20e98 · outbound

This paper cites Multi-task meta learning: learn how to adapt to unseen tasks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Multi-task meta learning: learn how to adapt to unseen tasks

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.947515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9eca7683-04e5-41ba-a6d2-9c79c977df74 · outbound

This paper cites Less is more towards parsimonious multi-task models using structured sparsity.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Less is more towards parsimonious multi-task models using structured sparsity

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.045921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b9b0c907-2cfd-4c2a-ba72-2400ba860aea · outbound

This paper cites Sharing to learn and learning to share; fitting together meta, multi-task, and transfer learning: A meta review.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Sharing to learn and learning to share; fitting together meta, multi-task, and transfer learning: A meta review

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.962538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5868162c-bf86-4cb8-9c87-6864415fd174 · outbound

This paper cites Neural pruning via growing regularization.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Neural pruning via growing regularization

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:49.020856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b57b5a3c-6f2c-4ab5-82e3-c4ba423f4514 · outbound

This paper cites Learning structured sparsity in deep neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning structured sparsity in deep neural networks

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.988331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d7e6a4f-0ef9-430c-bffc-1901ad07209e · outbound

This paper cites Learned optimizers that scale and generalize.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learned optimizers that scale and generalize

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:46.996696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a912c47-4bcd-440d-8128-ef25ded90e2e · outbound

This paper cites Learning to learn how to learn: Self-adaptive visual navigation using meta-learning.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning to learn how to learn: Self-adaptive visual navigation using meta-learning

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:48.967397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cabc4718-ada4-490a-862f-9267027ada03 · outbound

This paper cites Learning to schedule learning rate with graph neural networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning to schedule learning rate with graph neural networks

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:48.944643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5aafcdc1-fe8e-4112-b7ce-4386d1c3f836 · outbound

This paper cites Dilated residual networks.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Dilated residual networks

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:48.916181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5068a2d2-825f-4235-8797-5bc33ad9d5ae · outbound

This paper cites Model Selection and Estimation in Regression with Grouped Variables.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Model Selection and Estimation in Regression with Grouped Variables

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:47.035104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32f5d32c-2984-465b-80cd-57577318e54e · outbound

This paper cites Two heads are better than one: Boosting graph sparse training via semantic and topological awareness, 2024.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Two heads are better than one: Boosting graph sparse training via semantic and topological awareness, 2024

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:48.891428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aca49ff5-7e9e-4c51-b1c4-77cf7840e904 · outbound

This paper cites Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:47.051917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6cf58f5-654d-44a7-858f-c5dfc3b032cf · outbound

This paper cites Effective sparsification of neural networks with global sparsity constraint.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning Effective sparsification of neural networks with global sparsity constraint

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:35:48.849869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 330aaf2f-17be-456c-a66c-c81ecfed5533 · outbound

This paper cites To prune, or not to prune: exploring the efficacy of pruning for model compression.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning To prune, or not to prune: exploring the efficacy of pruning for model compression

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:47.068784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee18222e-58a5-4954-822d-b7c67e26be17 · outbound

This paper cites write newline.

Meta-Sparsity: Learning Optimal Sparse Structures in Multi-task Networks through Meta-learning write newline

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-10T17:35:47.079331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers