Peng Zhao
PulseAugur coverage of Peng Zhao — every cluster mentioning Peng Zhao across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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New research tackles dynamic regret in online learning with novel methods · 3 sources tracked
Three new research papers explore dynamic regret minimization in online learning settings. The first paper focuses on Follow-the-Regularized-Leader (FTRL) methods for curved losses and adaptive optimizers like Adam, pre…
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New arXiv papers advance multi-armed bandit algorithms and regret minimization
Multiple research papers published on arXiv explore advancements in multi-armed bandit algorithms. One paper addresses optimal switching regret for bandits with an oblivious adversary, proposing a single algorithm that …
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New algorithms offer improved regret bounds for online learning
A new research paper introduces algorithms for unconstrained online learning that offer improved regret bounds. These algorithms are parameter-free and achieve guarantees based on gradient variation, without needing pri…
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New algorithm LightONS improves efficiency for online exp-concave optimization
Researchers have developed LightONS, a new algorithm for online exp-concave optimization that maintains optimal regret bounds while significantly improving computational efficiency. Unlike the standard Online Newton Ste…