Layer-wise Quantization for Quantized Optimistic Dual Averaging | Paper Citation Record

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This paper cites write newline.

Layer-wise Quantization for Quantized Optimistic Dual Averaging write newline

Reference 1

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This paper cites https://developer.nvidia.com/nccl, 2023.

Layer-wise Quantization for Quantized Optimistic Dual Averaging https://developer.nvidia.com/nccl, 2023

Reference 2

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This paper cites https://www.open-mpi.org/, 2023.

Layer-wise Quantization for Quantized Optimistic Dual Averaging https://www.open-mpi.org/, 2023

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This paper cites Adaptive gradient communication via critical learning regime identification.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive gradient communication via critical learning regime identification

Reference 4

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Layer-wise Quantization for Quantized Optimistic Dual Averaging QSGD : Communication-efficient SGD via gradient quantization and encoding

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This paper cites An adaptive mirror-prox method for variational inequalities with singular operators.

Layer-wise Quantization for Quantized Optimistic Dual Averaging An adaptive mirror-prox method for variational inequalities with singular operators

Reference 6

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This paper cites Sifting through the noise: Universal first-order methods for stochastic variational inequalities.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Sifting through the noise: Universal first-order methods for stochastic variational inequalities

Reference 7

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Wasserstein generative adversarial networks

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This paper cites EfQAT: An Efficient Framework for Quantization-Aware Training.

Layer-wise Quantization for Quantized Optimistic Dual Averaging EfQAT: An Efficient Framework for Quantization-Aware Training

Reference 9

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive and self-confident on-line learning algorithms

Reference 10

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Levy, K

Reference 11

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 12

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This paper cites Distributed methods with compressed communication for solving variational inequalities, with theoretical guarantees.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed methods with compressed communication for solving variational inequalities, with theoretical guarantees

Reference 13

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Bregman proximal method for efficient communications under similarity, 2023 a

Reference 14

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This paper cites Stochastic gradient descent-ascent: Unified theory and new efficient methods.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Stochastic gradient descent-ascent: Unified theory and new efficient methods

Reference 15

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Pock, T

Reference 16

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This paper cites Reducing noise in gan training with variance reduced extragradient.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Reducing noise in gan training with variance reduced extragradient

Reference 17

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Online optimization with gradual variations

Reference 18

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 19

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Shanbhag, U

Reference 20

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Training GANs with Optimism

Reference 21

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Training GANs with optimism

Reference 22

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This paper cites New bounds for distributed mean estimation and variance reduction.

Layer-wise Quantization for Quantized Optimistic Dual Averaging New bounds for distributed mean estimation and variance reduction

Reference 23

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This paper cites S., Monga, R., Chen, K., Devin, M., Mao, M.

Layer-wise Quantization for Quantized Optimistic Dual Averaging S., Monga, R., Chen, K., Devin, M., Mao, M

Reference 24

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

Layer-wise Quantization for Quantized Optimistic Dual Averaging An image is worth 16x16 words: Transformers for image recognition at scale

Reference 25

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive subgradient methods for online learning and stochastic optimization

Reference 26

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Layer-wise Quantization for Quantized Optimistic Dual Averaging H., Abdelmoniem, A

Reference 27

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This paper cites Universal codeword sets and representations of the integers.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Universal codeword sets and representations of the integers

Reference 28

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Le Nguyen, H

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Pang, J.-S

Reference 30

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Layer-wise Quantization for Quantized Optimistic Dual Averaging M., and Ramezani-Kebrya, A

Reference 31

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Layer-wise Quantization for Quantized Optimistic Dual Averaging OPTQ : Accurate quantization for generative pre-trained transformers

Reference 32

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This paper cites A Variational Inequality Perspective on Generative Adversarial Networks.

Layer-wise Quantization for Quantized Optimistic Dual Averaging A Variational Inequality Perspective on Generative Adversarial Networks

Reference 33

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Layer-wise Quantization for Quantized Optimistic Dual Averaging A variational inequality perspective on generative adversarial networks

Reference 34

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Generative adversarial nets

Reference 35

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Accelerating distributed deep learning by adaptive gradient quantization

Reference 36

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Deep residual learning for image recognition

Reference 37

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Stochastic distributed learning with gradient quantization and double-variance reduction

Reference 38

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Explore aggressively, update conservatively: Stochastic extragradient methods with variable stepsize scaling

Reference 39

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive learning in continuous games: Optimal regret bounds and convergence to nash equilibrium

Reference 40

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Layer-wise Quantization for Quantized Optimistic Dual Averaging No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Reference 41

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

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Layer-wise Quantization for Quantized Optimistic Dual Averaging N., Jofr \'e , A., Oliveira, R

Reference 43

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Sidford, A

Reference 44

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Solving variational inequalities with stochastic mirror-prox algorithm

Reference 45

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Layer-wise Quantization for Quantized Optimistic Dual Averaging B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A

Reference 46

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Robust reinforcement learning via adversarial training with langevin dynamics

Reference 47

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Layer-wise Quantization for Quantized Optimistic Dual Averaging and Shanbhag, U

Reference 48

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Optimal algorithms for decentralized stochastic variational inequalities

Reference 51

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Learning multiple layers of features from tiny images

Reference 52

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Y., Yurtsever, A., and Cevher, V

Reference 53

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Det-cgd: Compressed gradient descent with matrix stepsizes for non-convex optimization

Reference 54

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Layer-wise Quantization for Quantized Optimistic Dual Averaging K., Talwalkar, A., and Smith, V

Reference 55

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Finite-time last-iterate convergence for multi-agent learning in games

Reference 56

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This paper cites Adaptive Compression for Communication-Efficient Distributed Training.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive Compression for Communication-Efficient Distributed Training

Reference 57

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Layer-wise Quantization for Quantized Optimistic Dual Averaging Projected reflected gradient methods for monotone variational inequalities

Reference 58

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This paper cites Golden ratio algorithms for variational inequalities.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Golden ratio algorithms for variational inequalities

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.703758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 86288cc2-73b2-4829-bfa1-64b4e1f7d790 · outbound

This paper cites Cgx: adaptive system support for communication-efficient deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Cgx: adaptive system support for communication-efficient deep learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.530413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9b0335c0-f150-449b-bdd8-7b00667940ad · outbound

This paper cites L-greco: Layerwise-adaptive gradient compression for efficient data-parallel deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging L-greco: Layerwise-adaptive gradient compression for efficient data-parallel deep learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.312236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dfe37ab8-21dc-4dba-91e4-ed849a7ba4cc · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:09.115269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac5b9f13-810a-460d-ab42-e95ee75c071f · outbound

This paper cites Adaptive Bound Optimization for Online Convex Optimization.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adaptive Bound Optimization for Online Convex Optimization

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:09.208938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 563fac6f-470a-49ad-ac05-2764683bcd32 · outbound

This paper cites Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:09.283738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03a86cd5-4450-4b8d-9527-b4e3b52e859c · outbound

This paper cites Intsgd: Adaptive floatless compression of stochastic gradients.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Intsgd: Adaptive floatless compression of stochastic gradients

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:22.044751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8396f1ff-a0d8-4ea3-a9b4-2b32175b678d · outbound

This paper cites Distributed learning with compressed gradient differences.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed learning with compressed gradient differences

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.903346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d8b6a7ac-b63d-4eec-8530-e3ded17bd7a5 · outbound

This paper cites A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach.

Layer-wise Quantization for Quantized Optimistic Dual Averaging A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:43:14.822487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b8b69285-041e-4f06-b101-ad7e7d7aee2d · outbound

This paper cites Convergence Rate of $\mathcal{O}(1/k)$ for Optimistic Gradient and Extra-gradient Methods in Smooth Convex-Concave Saddle Point Problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Convergence Rate of $\mathcal{O}(1/k)$ for Optimistic Gradient and Extra-gradient Methods in Smooth Convex-Concave Saddle Point Problems

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:43:14.596502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f874265f-2a4f-4b40-a9af-65d09ce3d5fa · outbound

This paper cites Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Prox-method with rate of convergence o(1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convex-concave saddle point problems

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.650281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a6cafcba-d9a3-4548-8794-478514bfbf45 · outbound

This paper cites Robust stochastic approximation approach to stochastic programming.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Robust stochastic approximation approach to stochastic programming

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:10.002753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 718f3028-35ad-46b8-8f6f-616af40f320f · outbound

This paper cites Introductory Lectures on Convex Optimization: A Basic Course.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Introductory Lectures on Convex Optimization: A Basic Course

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.403892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation be174f62-2a91-4269-917b-69e3dec80519 · outbound

This paper cites Dual extrapolation and its applications to solving variational inequalities and related problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Dual extrapolation and its applications to solving variational inequalities and related problems

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:21.176062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 64937844-11c0-4cc3-8ed6-704897adbd53 · outbound

This paper cites Primal-dual subgradient methods for convex problems.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Primal-dual subgradient methods for convex problems

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:20.933831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4ed56d01-4117-4f51-8b05-abeb8660b244 · outbound

This paper cites P., and Vian, J.

Layer-wise Quantization for Quantized Optimistic Dual Averaging P., and Vian, J

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:20.676144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ee935c71-e16f-44e0-9170-956515b9529b · outbound

This paper cites and Soltanolkotabi, M.

Layer-wise Quantization for Quantized Optimistic Dual Averaging and Soltanolkotabi, M

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:10.574048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c37b09d-373c-4f86-86ef-53eee291e73c · outbound

This paper cites Training GANs with Centripetal Acceleration.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Training GANs with Centripetal Acceleration

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:43:14.308019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ac913823-8ccc-402e-b701-4b80d8eef385 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:20.465765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 622ea920-5af3-41f8-92a3-f8e2bfa301ef · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 78

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:20.154546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9207e963-4c25-4189-be86-c0a7a07670e0 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:19.888901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e63ac9d0-ec28-4c84-9dfb-27e02831a853 · outbound

This paper cites Mixtailor: Mixed gradient aggregation for robust learning against tailored attacks.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Mixtailor: Mixed gradient aggregation for robust learning against tailored attacks

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:19.654986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7c3bc914-4d3c-4b61-af4c-2f131eb7ec56 · outbound

This paper cites Distributed extra-gradient with optimal complexity and communication guarantees.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed extra-gradient with optimal complexity and communication guarantees

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:19.367968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 61a4f09c-e666-4da6-b747-76f7801ea6fa · outbound

This paper cites Adversarially robust generalization requires more data.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Adversarially robust generalization requires more data

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:19.109312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 30847bc3-2da2-493d-ad5f-476810a26007 · outbound

This paper cites Scalable distributed DNN training using commodity GPU cloud computing.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Scalable distributed DNN training using commodity GPU cloud computing

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:18.862111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a73608f-6dcd-44b2-be56-50ba7315f390 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 84

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:18.632188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 37aa223e-64f9-4bdd-8eee-65ae1bbc0c4f · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:18.403526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ff5fbdd6-bf07-4887-8d2d-ae476ac35091 · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:43:18.182723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71010c99-57e4-434d-b844-f4db42d91522 · outbound

This paper cites J., Wu, Y., Takac, M., Nandakumar, K., Horv \'a th, S., and Gorbunov, E.

Layer-wise Quantization for Quantized Optimistic Dual Averaging J., Wu, Y., Takac, M., Nandakumar, K., Horv \'a th, S., and Gorbunov, E

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:17.976108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 76988e9f-92f5-435e-86e6-eb7b0cea34e1 · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

Layer-wise Quantization for Quantized Optimistic Dual Averaging N., Kaiser, ., and Polosukhin, I

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:17.777565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d9f84d80-1e66-4e50-9ce7-fafbabcb4d22 · outbound

This paper cites Delay jitter control for real-time communication in a packet switching network.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Delay jitter control for real-time communication in a packet switching network

Reference 89

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T15:43:14.027735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a0b54fc-c5c3-4e5d-8f47-bcf18ac3611a · outbound

This paper cites Theoretically better and numerically faster distributed optimization with smoothness-aware quantization techniques.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Theoretically better and numerically faster distributed optimization with smoothness-aware quantization techniques

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:17.601636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cca203ec-4551-4432-a41b-b23067525c50 · outbound

This paper cites Atomo: Communication-efficient learning via atomic sparsification.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Atomo: Communication-efficient learning via atomic sparsification

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:17.284463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ea5e5166-b618-4891-af95-36d9e5da89a9 · outbound

This paper cites TernGrad : Ternary gradients to reduce communication in distributed deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging TernGrad : Ternary gradients to reduce communication in distributed deep learning

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:17.025567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eb5de229-bfdf-4a4d-8ea9-33112ddd8d17 · outbound

This paper cites E., Bullins, B., Shamir, O., and Srebro, N.

Layer-wise Quantization for Quantized Optimistic Dual Averaging E., Bullins, B., Shamir, O., and Srebro, N

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:16.707106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7c723383-0876-4df6-84d5-89e3f876f678 · outbound

This paper cites Mixed nash for robust federated learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Mixed nash for robust federated learning

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:16.478937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d2c99ca3-953c-499c-a075-de948e352c1a · outbound

This paper cites Kimad: Adaptive gradient compression with bandwidth awareness.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Kimad: Adaptive gradient compression with bandwidth awareness

Reference 95

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T15:43:13.718731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7e2eb9d5-bf51-4950-bce0-d761299755a5 · outbound

This paper cites Block-Normalized Gradient Method: An Empirical Study for Training Deep Neural Network.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Block-Normalized Gradient Method: An Empirical Study for Training Deep Neural Network

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:12.951097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f045445-e606-4512-bc09-5b4ba8b90d4d · outbound

This paper cites Distributed dual averaging method for multi-agent optimization with quantized communication.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Distributed dual averaging method for multi-agent optimization with quantized communication

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:16.276048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2ac9c2f7-17dc-41c8-833d-6bdfc4f3f85a · outbound

This paper cites an unresolved cited work.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Unresolved cited work

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:13.145080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18fa1f5b-c047-4bf3-b6d0-db2b1393db3c · outbound

This paper cites Understanding deep learning (still) requires rethinking generalization.

Layer-wise Quantization for Quantized Optimistic Dual Averaging Understanding deep learning (still) requires rethinking generalization

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:13.226800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b777c825-a9e3-49bc-911c-fa53e21f9b12 · outbound

This paper cites ZipML : Training linear models with end-to-end low precision, and a little bit of deep learning.

Layer-wise Quantization for Quantized Optimistic Dual Averaging ZipML : Training linear models with end-to-end low precision, and a little bit of deep learning

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:43:16.069577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Reference resolution

Outbound references

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