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Showing papers from Lomonosov Moscow State University Show all papers

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NeurIPS 2026Lomonosov Moscow StateDeep learning theory

Information bottleneck dynamics during learning across artificial and biological neural systems

Nikita Pospelov, Olga Ivashkina, Plusnin Viktor, Olga Rogozhnikova and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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67%Highly rated
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NeurIPS 2026Huawei Technologies Ltd.Lomonosov Moscow StatePruning & sparsity

SVDP: Training-Free Contextual Sparsity Predictors for Fast LLM Inference

Georgii Serbin, Kirill Koshkin, Zhongao Sun, Anastasiya Bistrigova and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look
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NeurIPS 2026OralLomonosov Moscow StateOptimization

Do We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods

Grigory Begunov, Alexander Tyurin

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Lomonosov Moscow StateHuawei Technologies Ltd.Moscow State University, LomonosInnopolisImage restoration

SR-Prominence: A Crowdsourced Protocol and Dataset Suite for Perceptually-Weighted Super-Resolution Artifact Evaluation

SR-Prominence defines artifact prominence via crowdsourced annotations across 3,935 masks and shows classical full-reference metrics surprisingly detect perceptual impact better than specialized detectors.

Ivan Molodetskikh, Kirill Malyshev, Mark Mirgaleev, Nikita Zagainov and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 19 of 20 reviewers recommend it
lenient 5/5
medium 9/10
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72%Highly rated
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NeurIPS 2026Lomonosov Moscow StateEfficient & distributed training

Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits

Proposing Inkheart SGD and M4 with structural assumptions achieves distributed compressed optimization complexities scaling with workers n and surpassing pessimistic lower bounds.

Grigory Begunov, Alexander Tyurin

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 8 of 20 reviewers recommend it
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