Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation | Paper Citation Record

Observation 6166f0fb-9fed-4ecd-b784-e872f8ca36bc · outbound

This paper cites Oblivious sketching of high-degree polynomial kernels.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Oblivious sketching of high-degree polynomial kernels

Reference 1

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This paper cites The fast johnson--lindenstrauss transform and approximate nearest neighbors.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation The fast johnson--lindenstrauss transform and approximate nearest neighbors

Reference 2

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This paper cites Katyusha: The first direct acceleration of stochastic gradient methods.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Katyusha: The first direct acceleration of stochastic gradient methods

Reference 3

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This paper cites The space complexity of approximating the frequency moments.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation The space complexity of approximating the frequency moments

Reference 4

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This paper cites Nguyen, and David P.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Nguyen, and David P

Reference 5

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This paper cites Clarkson, and David P.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Clarkson, and David P

Reference 6

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This paper cites Random fourier features for kernel ridge regression: Approximation bounds and statistical guarantees.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Random fourier features for kernel ridge regression: Approximation bounds and statistical guarantees

Reference 7

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 8

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This paper cites Harmonic Analysis and the Theory of Probability.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Harmonic Analysis and the Theory of Probability

Reference 9

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This paper cites AMS without 4-wise independence on product domains.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation AMS without 4-wise independence on product domains

Reference 10

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This paper cites Convex optimization: Algorithms and complexity.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Convex optimization: Algorithms and complexity

Reference 11

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 12

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This paper cites LIBSVM : A library for support vector machines.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation LIBSVM : A library for support vector machines

Reference 13

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This paper cites Hashing-based-estimators for kernel density in high dimensions.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Hashing-based-estimators for kernel density in high dimensions

Reference 14

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This paper cites Finding frequent items in data streams.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Finding frequent items in data streams

Reference 15

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This paper cites Colwell, and Adrian Weller.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Colwell, and Adrian Weller

Reference 16

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This paper cites Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Tensor networks for dimensionality reduction and large-scale optimization: Part 1 low-rank tensor decompositions

Reference 17

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This paper cites Kernel pooling for convolutional neural networks.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Kernel pooling for convolutional neural networks

Reference 18

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This paper cites Learning to evaluate image captioning.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Learning to evaluate image captioning

Reference 19

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 20

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 21

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This paper cites Woodruff.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Woodruff

Reference 22

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This paper cites KONG: kernels for ordered-neighborhood graphs.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation KONG: kernels for ordered-neighborhood graphs

Reference 23

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This paper cites LIBLINEAR : A library for large linear classification.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation LIBLINEAR : A library for large linear classification

Reference 24

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This paper cites Scalable attributed-graph subspace clustering.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Scalable attributed-graph subspace clustering

Reference 25

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This paper cites What can a single attention layer learn? a study through the random features lens.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation What can a single attention layer learn? a study through the random features lens

Reference 26

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This paper cites Multimodal compact bilinear pooling for visual question answering and visual grounding.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Multimodal compact bilinear pooling for visual question answering and visual grounding

Reference 27

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This paper cites Compact bilinear pooling.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Compact bilinear pooling

Reference 28

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 29

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This paper cites Compact random feature maps.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Compact random feature maps

Reference 30

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This paper cites Polynomial tensor sketch for element-wise function of low-rank matrix.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Polynomial tensor sketch for element-wise function of low-rank matrix

Reference 31

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This paper cites Declaring independence via the sketching of sketches.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Declaring independence via the sketching of sketches

Reference 32

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This paper cites Text categorization with support vector machines: Learning with many relevant features.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Text categorization with support vector machines: Learning with many relevant features

Reference 33

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This paper cites Training linear SVM s in linear time.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Training linear SVM s in linear time

Reference 34

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This paper cites Fast alignment-free similarity estimation by tensor sketching.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Fast alignment-free similarity estimation by tensor sketching

Reference 35

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This paper cites Random feature maps for dot product kernels.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Random feature maps for dot product kernels

Reference 36

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This paper cites Algorithm Design.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Algorithm Design

Reference 37

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This paper cites Principled neuromorphic reservoir computing.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Principled neuromorphic reservoir computing

Reference 38

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This paper cites Sampling methods for the N ystr \" o m method.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Sampling methods for the N ystr \" o m method

Reference 39

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This paper cites Lewis, Yiming Yang, Tony G.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Lewis, Yiming Yang, Tony G

Reference 40

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This paper cites Sgm-net: Skeleton-guided multimodal network for action recognition.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Sgm-net: Skeleton-guided multimodal network for action recognition

Reference 41

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This paper cites Towards a unified analysis of random fourier features.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Towards a unified analysis of random fourier features

Reference 42

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

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This paper cites Smola, Zoubin Ghahramani, and Bernhard Sch \" o lkopf.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Smola, Zoubin Ghahramani, and Bernhard Sch \" o lkopf

Reference 46

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 47

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This paper cites Low-rank tucker decomposition of large tensors using tensorsketch.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Low-rank tucker decomposition of large tensors using tensorsketch

Reference 48

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This paper cites Randomized numerical linear algebra: Foundations and algorithms.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Randomized numerical linear algebra: Foundations and algorithms

Reference 49

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Woodruff

Reference 50

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This paper cites Kernel mean embedding of distributions: A review and beyond.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Kernel mean embedding of distributions: A review and beyond

Reference 51

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This paper cites An improved training algorithm for support vector machines.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation An improved training algorithm for support vector machines

Reference 52

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This paper cites Compressed matrix multiplication.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Compressed matrix multiplication

Reference 53

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This paper cites Pedregosa, G.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Pedregosa, G

Reference 54

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This paper cites Yu, and Sanjiv Kumar.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Yu, and Sanjiv Kumar

Reference 55

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This paper cites Fast and scalable polynomial kernels via explicit feature maps.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Fast and scalable polynomial kernels via explicit feature maps

Reference 56

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This paper cites The power of simple tabulation hashing.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation The power of simple tabulation hashing

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.284373Z

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Random features for large-scale kernel machines

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.271466Z

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Learning action recognition model from depth and skeleton videos

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.259745Z

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This paper cites Generalization properties of learning with random features.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Generalization properties of learning with random features

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.246489Z

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This paper cites A spectral analysis of dot-product kernels.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation A spectral analysis of dot-product kernels

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.235007Z

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 62

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Learning with Kernels: support vector machines, regularization, optimization, and beyond

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.221556Z

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation High-order attention models for visual question answering

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.209307Z

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This paper cites Pegasos: P rimal estimated sub-gradient solver for SVM.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Pegasos: P rimal estimated sub-gradient solver for SVM

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.197994Z

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Kernel Methods for Pattern Analysis

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.185644Z

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This paper cites Higher-order count sketch: Dimensionality reduction that retains efficient tensor operations.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Higher-order count sketch: Dimensionality reduction that retains efficient tensor operations

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.174068Z

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This paper cites Relative error tensor low rank approximation.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Relative error tensor low rank approximation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.160677Z

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Sriperumbudur and Nicholas Sterge

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.147240Z

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Observation 3802ebb8-a7eb-49f7-8b9b-52b8aaa71332 · outbound

This paper cites Sriperumbudur and Zolt \' a n Szab \' o.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Sriperumbudur and Zolt \' a n Szab \' o

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.134890Z

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Observation 21e4ae2e-dcc0-44f8-8522-74f4fc7a3625 · outbound

This paper cites Few-shot learning for domain-specific fine-grained image classification.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Few-shot learning for domain-specific fine-grained image classification

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.122648Z

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This paper cites Gilbert, and Ambuj Tewari.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Gilbert, and Ambuj Tewari

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.110779Z

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This paper cites Tabulation-based 5-independent hashing with applications to linear probing and second moment estimation.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Tabulation-based 5-independent hashing with applications to linear probing and second moment estimation

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.099947Z

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Observation 1a60b980-b47a-4008-b1af-d24e36b9cf9e · outbound

This paper cites Tanimoto random features for scalable molecular machine learning.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Tanimoto random features for scalable molecular machine learning

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.087944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:15:35.075829Z

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This paper cites Smola, and Anima Anandkumar.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Smola, and Anima Anandkumar

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.063949Z

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Observation bef60109-0ca2-4b62-b2a1-dfa857cecd4b · outbound

This paper cites Weinberger, Anirban Dasgupta, John Langford, Alexander J.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Weinberger, Anirban Dasgupta, John Langford, Alexander J

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.050835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0323accd-c1c2-44e9-bc85-b64e1e317e31 · outbound

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Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:15:35.038398Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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This paper cites Woodruff.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Woodruff

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.025117Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 34164961-b105-4f47-9d86-20a52b410039 · outbound

This paper cites Aggarwal.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Aggarwal

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:35.011941Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 997aab76-654e-4c2c-a7f8-877fd93c751f · outbound

This paper cites Scalable DBSCAN with random projections.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Scalable DBSCAN with random projections

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:34.999423Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2e3929fe-d0d8-4e83-a1d0-7fc5ab5be764 · outbound

This paper cites Nystr \"o m method vs random fourier features: A theoretical and empirical comparison.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Nystr \"o m method vs random fourier features: A theoretical and empirical comparison

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:34.986977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bdcb3bf1-b22f-415c-a193-91daf0471683 · outbound

This paper cites On the power and limitations of random features for understanding neural networks.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation On the power and limitations of random features for understanding neural networks

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:34.974405Z

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Observation 1b4cd4b5-b943-44f2-8ddf-228e61fb9f16 · outbound

This paper cites Scaling neural tangent kernels via sketching and random features.

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Scaling neural tangent kernels via sketching and random features

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:15:34.960339Z

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