This paper presents a deterministic algorithm achieving an expected competitive ratio of O(1) for Euclidean online TSP in high dimensions and O(log n) for d = 1, improving upon previous O(sqrt(n)) and…

This paper studies learning-augmented online weighted vertex cover with advice and presents algorithms for bipartite and general graphs.

This paper presents deterministic and randomized algorithms for the incremental dominating set problem in vertex-weighted graphs, achieving competitive ratios of O(Δ) and O(log^2Δ) respectively. It al…

This paper studies online stochastic matching in an edge arrival model, showing that competitive ratios better than 1-1/e are possible.

A simple online algorithm is presented for the stacking problem to avoid shifts with a sufficient condition involving stacking area dimension, load/unload points, and maximum items.

This paper studies fair online resource allocation with a Lipschitz fairness requirement and proposes an algorithm to maximize welfare while enforcing fairness.

The paper provides improved bounds on the discrepancy of the online carpooling problem.

The paper presents a constant-competitive algorithm for the Matroid Secretary Problem on graphic matroids using only an independence oracle.

This paper shows that stochastic nonconvex optimization can be reduced to ordinary static regret minimization in online convex optimization, and establishes convergence rates for smooth and Lipschitz…

This paper proposes HT-PAder, a parameter-free algorithm for online convex optimization in non-stationary environments with heavy-tailed noise, achieving an expected universal dynamic regret.

This paper improves the worst-case regret in Online Convex Optimization (OCO) by introducing a unified probing model with a budget of pairwise probes.

The paper re-examines the Parking Permit Problem using the primal-dual scheme, obtaining simple algorithms with superior performance guarantees and providing near-matching lower bounds.

The paper presents an adaptive scaling algorithm with a competitive ratio of 1.373 for incremental submodular maximization under increasing cardinality constraint, improving upon the previous best res…