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Papers

Publications linked to models, labs and benchmarks. Authors, venues and abstracts come from arXiv and publisher pages.

12 total

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Papers
TitleAuthorsPublishedCategoriesOrganization / venueQuality
Certifying Lower Bounds for Risk-Sensitive Reinforcement Learning under Adversarial State PerturbationsarXiv:2609.10866Tong Li, Saunak Kumar Panda, Yisha Xiang11 Sept 2026cs.LG
EGGROLL, Unrolled: Understanding and Improving Low-Rank Evolution Strategies at ScalearXiv:2609.10980Ege C. Kaya, Abolfazl Hashemi11 Sept 2026cs.LG
Convex Optimization with Nested Evolving Feasible Sets (CONES) under Time-Varying Loss FunctionsarXiv:2609.11207Rahul Vaze11 Sept 2026cs.LG
AdamX: Cosine similarity meets gradient descentarXiv:2609.11867Francisco Caldas, Ruben Belo, Cl\'audia Soares11 Sept 2026cs.LG
EVTradeMatch: A Mobility-Aware Multi-Objective Matching Framework for EV--EV Energy TradingarXiv:2609.10551Md. Mahfujur Rahman, Alistair Barros, Raja Jurdak +111 Sept 2026math.OC
Supply Chain Analytics: A Data-Driven ApproacharXiv:2609.10563Elioth Sanabria11 Sept 2026math.OC
Sparsity Regularized and Robust Mean Variance Portfolio Selection Under Ellipsoidal UncertaintyarXiv:2609.11749Deniz Akkaya, Emre Can Yayla, Buse \c{S}en +111 Sept 2026math.OC
Monotone Neural Policy Iteration for High-Dimensional First-Order Hamilton--Jacobi--Bellman EquationsarXiv:2605.07116Minseok Kim, Yeongjong Kim, Namkyeong Cho +111 Sept 2026cs.LG
Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy GradientsarXiv:2403.19448Johannes M\"uller, Semih \c{C}ayc{\i}, Guido Mont\'ufar11 Sept 2026math.OC
VALG: An Agentic System for ML Theory ResearcharXiv:2608.13060Dechen Zhang, Xuan Tang, Xinxiang Yin +211 Sept 2026cs.AI
Silver Rate Is (Almost) Optimal for Gradient DescentarXiv:2609.09152Yuhan Ye, Kaizhao Liu11 Sept 2026math.OC
Support Discovery With Iteratively Reweighted Least Squares for Fixed-Charge Network FlowarXiv:2609.09295Sindura Saraswathi, Christian K\"ummerle11 Sept 2026math.OC

12 results

Author lists and categories are copied from the paper's own metadata (arXiv, publisher). Each paper page shows the abstract, related models and every source snapshot.