Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior | Paper Citation Record

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Distributed variational representation learning

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Alemi, Ian Fischer, Joshua V

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior User-friendly introduction to PAC-Bayes bounds

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior An exact characterization of the generalization error for the gibbs algorithm

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Learning representations for neural network-based classification using the information bottleneck principle

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Stronger generalization bounds for deep nets via a compression approach

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior K-means++: The advantages if careful seeding

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Heavy tails in SGD and compressibility of overparametrized neural networks

Reference 8

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pac-bayesian bounds based on the r \'e nyi divergence

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior On the Convergence of the Empirical Distribution

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Intrinsic dimension, persistent homology and generalization in neural networks

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pac-mdl bounds

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Occam's razor

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Proper learning, helly number, and an optimal svm bound

Reference 14

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Veeravalli

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A pac-bayesian approach to adaptive classification

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Learning with metric losses

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This paper cites A novel approach for effective multi-view clustering with information-theoretic perspective.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A novel approach for effective multi-view clustering with information-theoretic perspective

Reference 18

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Approximating priors by mixtures of natural conjugate priors

Reference 19

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Asymptotic evaluation of certain markov process expectations for large time, i

Reference 20

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This paper cites Learning optimal representations with the decodable information bottleneck.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Learning optimal representations with the decodable information bottleneck

Reference 21

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data

Reference 22

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Data-dependent pac-bayes priors via differential privacy

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Generalization error bounds via R \'enyi-, f -divergences and maximal leakage, 2020

Reference 24

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Distributed information bottleneck method for discrete and gaussian sources

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Learning Robust Representations via Multi-View Information Bottleneck

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior The conditional entropy bottleneck

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior On information plane analyses of neural network classifiers--a review

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior On the information dimension of stochastic processes

Reference 29

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pac-bayesian learning of linear classifiers

Reference 30

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Understanding the difficulty of training deep feedforward neural networks

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Estimating information flow in deep neural networks

Reference 32

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Deep learning, 2016

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Limitations of information-theoretic generalization bounds for gradient descent methods in stochastic convex optimization

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A sharp lower bound for agnostic learning with sample compression schemes

Reference 36

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Stable sample compression schemes: New applications and an optimal svm margin bound

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Sample compression for real-valued learners

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Universal bayes consistency in metric spaces

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Information-theoretic generalization bounds for black-box learning algorithms

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A new family of generalization bounds using samplewise evaluated cmi

Reference 41

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Approximating the kullback leibler divergence between gaussian mixture models

Reference 42

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Generalization bounds using lower tail exponents in stochastic optimizers

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Generalization bounds via distillation

Reference 44

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A survey on information bottleneck

Reference 45

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior On the multi-view information bottleneck representation

Reference 46

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Generalized information-theoretic multi-view clustering

Reference 47

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Auto-encoding variational bayes

Reference 51

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Gacs-Korner Common Information Variational Autoencoder

Reference 52

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Caveats for information bottleneck in deterministic scenarios

Reference 53

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Nonlinear information bottleneck

Reference 54

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Learning multiple layers of features from tiny images

Reference 55

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior (not) bounding the true error

Reference 56

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This paper cites Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Chaotic Regularization and Heavy-Tailed Limits for Deterministic Gradient Descent

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:33:43.240441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation adec61e9-9a89-45fb-b6ee-c448eb6e4863 · outbound

This paper cites Dual contrastive prediction for incomplete multi-view representation learning.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Dual contrastive prediction for incomplete multi-view representation learning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.972347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9f54fe4b-c895-4736-897e-eac498f5e2e0 · outbound

This paper cites Relating data compression and learnability.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Relating data compression and learnability

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.958984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 430068c3-0344-4d08-8e69-ac2969b598c9 · outbound

This paper cites Information theoretic lower bounds for information theoretic upper bounds.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Information theoretic lower bounds for information theoretic upper bounds

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.947375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 959b535e-f814-4478-b41c-a7724e7d5cbb · outbound

This paper cites Generalization bounds via convex analysis.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Generalization bounds via convex analysis

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.909830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5c1495cf-d4bd-482c-a0f4-e49ee7895d74 · outbound

This paper cites Recognizable Information Bottleneck.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Recognizable Information Bottleneck

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:41.755383Z

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Observation 4bb39a32-6084-454b-8406-ac3c69d73c50 · outbound

This paper cites A Note on the PAC Bayesian Theorem.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A Note on the PAC Bayesian Theorem

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:41.760441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9207dc84-e70b-4fb1-bd55-b20dc4c1e152 · outbound

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Communication-efficient learning of deep networks from decentralized data

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:41.763973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54f3d057-f528-4e3e-907e-f17c17085d96 · outbound

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior In-network learning for distributed training and inference in networks

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.833361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2c180361-9112-4b70-8512-434e5faec82f · outbound

This paper cites In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior In defense of uniform convergence: Generalization via derandomization with an application to interpolating predictors

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.821586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1f06a024-b0e3-4eae-8bc6-1661d1e90fe5 · outbound

This paper cites an unresolved cited work.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:33:44.810062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57d4fb4b-5074-44e4-b189-05a3eabafc1b · outbound

This paper cites an unresolved cited work.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-16T10:33:44.799006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cea4cde4-7a00-4718-a0ae-01db9fd818c0 · outbound

This paper cites A pac-bayesian approach to spectrally-normalized margin bounds for neural networks, 2018.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A pac-bayesian approach to spectrally-normalized margin bounds for neural networks, 2018

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.787728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 793f5a22-9486-4af8-b9cd-4c1a8dcec8ed · outbound

This paper cites Improving transformers with probabilistic attention keys.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Improving transformers with probabilistic attention keys

Reference 70

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b525ca2c-d26f-4c9e-a7f6-87fd64b05a8a · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pytorch: An imperative style, high-performance deep learning library

Reference 71

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb923052-97c7-43c2-b70b-a362ee3afd15 · outbound

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Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Tighter risk certificates for neural networks

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.600221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bb66c8cf-30da-4499-a890-7138131b0c7e · outbound

This paper cites Pac-bayes analysis beyond the usual bounds.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pac-bayes analysis beyond the usual bounds

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.590060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d4cb5ae0-111c-446b-817d-54011337ea5e · outbound

This paper cites The information bottleneck: Connections to other problems, learning and exploration of the ib curve, 2019.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior The information bottleneck: Connections to other problems, learning and exploration of the ib curve, 2019

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.580780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94d2d8c2-0ce2-4579-9132-e6ad9dc785f9 · outbound

This paper cites The convex information bottleneck lagrangian.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior The convex information bottleneck lagrangian

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.570731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6fa527e1-6939-4422-85ac-3597829a51a8 · outbound

This paper cites Controlling bias in adaptive data analysis using information theory.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Controlling bias in adaptive data analysis using information theory

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.559550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5e9e9a4-ae9c-4b9f-b02a-54330ef313fd · outbound

This paper cites Pac-bayesian generalisation error bounds for gaussian process classification.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pac-bayesian generalisation error bounds for gaussian process classification

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.473808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ead870ee-952a-47f0-8b45-3f4a90aafa11 · outbound

This paper cites Data-dependent generalization bounds via variable-size compressibility.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Data-dependent generalization bounds via variable-size compressibility

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.428370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3e85b3f4-6768-400a-89b0-c64cc499e1a5 · outbound

This paper cites Rate-distortion theoretic generalization bounds for stochastic learning algorithms.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Rate-distortion theoretic generalization bounds for stochastic learning algorithms

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.415181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2704937f-8f3d-4abc-b538-bb87fdcd8b95 · outbound

This paper cites Minimum description length and generalization guarantees for representation learning.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Minimum description length and generalization guarantees for representation learning

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.400532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 55156308-8ce4-4221-8669-509f675e42f3 · outbound

This paper cites Generalization guarantees for representation learning via data-dependent gaussian mixture priors.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Generalization guarantees for representation learning via data-dependent gaussian mixture priors

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.319380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 12c591d9-d427-4e56-9e91-3acfd2d205f5 · outbound

This paper cites Learning and generalization with the information bottleneck.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Learning and generalization with the information bottleneck

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.305771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5c0135a-7c32-4c9a-ac8e-6c5703c713b1 · outbound

This paper cites Hausdorff dimension, heavy tails, and generalization in neural networks.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Hausdorff dimension, heavy tails, and generalization in neural networks

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.204218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c4a9a3e0-e805-4490-af65-eab3b37c0e0e · outbound

This paper cites R easoning about generalization via conditional mutual information.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior R easoning about generalization via conditional mutual information

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.191894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e570ad8a-6198-4584-8282-049b12ce3838 · outbound

This paper cites Spectral pruning: Compressing deep neural networks via spectral analysis and its generalization error.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Spectral pruning: Compressing deep neural networks via spectral analysis and its generalization error

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.139514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 44995e5f-9249-41e7-9e69-28851e8f4ff3 · outbound

This paper cites A strongly quasiconvex pac-bayesian bound.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A strongly quasiconvex pac-bayesian bound

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:44.018735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 927616cc-50e1-4401-83eb-41192c2614c5 · outbound

This paper cites The information bottleneck method.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior The information bottleneck method

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.324089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e09c14f2-5af3-496e-9c92-3289dc210ca0 · outbound

This paper cites Pac-bayes-empirical-bernstein inequality.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Pac-bayes-empirical-bernstein inequality

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:43.956209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 830fd09f-b594-46b8-a7c5-d1733deb0825 · outbound

This paper cites The role of the information bottleneck in representation learning.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior The role of the information bottleneck in representation learning

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.332646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b412d64-39eb-4ef3-af4f-ba299fc06a77 · outbound

This paper cites A General Framework for the Practical Disintegration of PAC-Bayesian Bounds.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior A General Framework for the Practical Disintegration of PAC-Bayesian Bounds

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.336555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 569035c9-5fa8-41bb-b238-3d6db8a18a63 · outbound

This paper cites Multi-view information-bottleneck representation learning.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Multi-view information-bottleneck representation learning

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:43.941167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d6678c2e-8e72-4e19-9d35-b0180fd96967 · outbound

This paper cites Cross-view representation learning for multi-view logo classification with information bottleneck.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Cross-view representation learning for multi-view logo classification with information bottleneck

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:43.757065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b8cc3850-598b-4aa0-8c35-213340ce5457 · outbound

This paper cites Deep multi-view information bottleneck.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Deep multi-view information bottleneck

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:43.684251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3e0b38e7-0c75-4ec4-b53d-34361c523be3 · outbound

This paper cites Information-theoretic analysis of generalization capability of learning algorithms.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Information-theoretic analysis of generalization capability of learning algorithms

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:43.673162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe6fd27e-58c6-4d20-8595-6931ab3d3ebb · outbound

This paper cites Deep multi-view learning methods: A review.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Deep multi-view learning methods: A review

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.625531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41385a65-5522-4bfc-83bb-7fda2fe866b1 · outbound

This paper cites Differentiable Information Bottleneck for Deterministic Multi-view Clustering.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Differentiable Information Bottleneck for Deterministic Multi-view Clustering

Reference 96

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:33:43.014768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26131e1a-149a-490b-aedc-ef8c9158ce12 · outbound

This paper cites On the information bottleneck problems: Models, connections, applications and information theoretic views.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior On the information bottleneck problems: Models, connections, applications and information theoretic views

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:33:43.613946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 536923f7-8c2f-49db-a25e-7fe073031f1e · outbound

This paper cites Individually conditional individual mutual information bound on generalization error.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Individually conditional individual mutual information bound on generalization error

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.637514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de9defe3-d258-47aa-b316-6f45679e9921 · outbound

This paper cites @esa (Ref.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior @esa (Ref

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.641494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96886cf0-f0b7-45df-a3be-f8d9f6edc05d · outbound

This paper cites an unresolved cited work.

Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Unresolved cited work

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-16T10:33:42.646053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Reference resolution

Outbound references

Pith citing papers