arXiv:2509. 07779v2 Announce Type: replace-cross Abstract: We study decentralized online Riemannian optimization over manifolds with possibly positive curvature, going beyond the Hadamard manifold setting.
By Emre Sahinoglu, Shahin Shahrampour
arXiv:2609. 13646v1 Announce Type: new Abstract: This work addresses decentralized online Riemannian optimization on Hadamard manifolds.
By Zhanyuan Cai, Emre Sahinoglu, Shahin Shahrampour
arXiv:2601.13519v4 Announce Type: replace-cross
Abstract: This paper introduces a new problem-dependent regret measure for online convex optimization with smooth losses. The notion, which we call the...
By Wenzhi Gao, Chang He, Madeleine Udell
arXiv:2606. 02948v1 Announce Type: new Abstract: Curvature adaptivity is a classical theme in online optimization: for convex Lipschitz losses, adaptive methods interpolate between the optimal $O(\sqrt{T})$ regret for general convex losses and $O(\log T)$ regret under strong convexity.
By Moses Charikar, Chirag Pabbaraju, Ambuj Tewari
arXiv:2605. 21107v2 Announce Type: replace Abstract: We study constrained online convex optimization with adversarial time-varying constraints.
By Dhruv Sarkar, Abhishek Sinha
arXiv:2607. 14731v1 Announce Type: new Abstract: Local SGD, also known as Federated Averaging, is a widely used distributed optimization algorithm.
By Kumar Kshitij Patel, Rustem Islamov, Sebastian U Stich, Aurelien Lucchi, Eduard Gorbunov, Lingxiao Wang