45%Niche pick?Niche pickVote to see the scoreNeurIPS 2026Boston University, BostonCelonisUniversität KölnNational Institute of InformaticOptimizationStable Max Coverage Under a Cardinality ConstraintThemistoklis Haris, Fabian Spaeh, Nithin Varma, Yuichi YoshidaSydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet0/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 0 of 20 reviewers recommend itlenient 0/5medium 0/10strict 0/5
76%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026YaleGoogle ResearchNational Institute of InformaticOptimizationPointwise Lipschitz Continuous Graph AlgorithmsThis paper proposes a linear programming-based minimum s-t cut algorithm with an optimal Lipschitz constant, yielding the first dynamic algorithm with non-trivial recourse and improved b-matching stability.Quanquan C Liu, Grigoris Velegkas, Yuichi Yoshida, Felix ZhouAtlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026– ReadersNo votes yet10/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 10 of 20 reviewers recommend itlenient 3/5medium 6/10strict 1/5
70%Highly rated?Highly ratedVote to see the scoreNeurIPS 2026OralCyberAgent, NII, RIKEN AIPNational Institute of InformaticLearning theoryFrom Average Sensitivity to Small-Loss Regret Bounds under Random-Order ModelAverage sensitivity of offline approximations yields small-loss regret bounds via batch-to-online conversion in random-order online learning.Shinsaku Sakaue, Yuichi YoshidaSydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026– ReadersNo votes yet5/20 AI panelreviewers recommend itReaders and the AI panel: vote on this paper to see what they said.Worth readingNot for meOnly vote on papers you've read. Sign in with GitHub to vote.AI panel: 5 of 20 reviewers recommend itlenient 2/5medium 2/10strict 1/5