| Bandits with Feedback Graphs and Switching Costs | Raman Arora · Teodor Vanislavov Marinov · Mehryar Mohri |
| Batched Multi-armed Bandits Problem | Zijun Gao · Yanjun Han · Zhimei Ren · Zhengqing Zhou |
| Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization | Gautam Goel · Yiheng Lin · Haoyuan Sun · Adam Wierman |
| Equipping Experts/Bandits with Long-term Memory | Kai Zheng · Haipeng Luo · Ilias Diakonikolas · Liwei Wang |
| Large Scale Markov Decision Processes with Changing Rewards | Adrian Rivera Cardoso · He Wang · Huan Xu |
| Online Learning via the Differential Privacy Lens | Jacob Abernethy · Young Hun Jung · Chansoo Lee · Audra McMillan · Ambuj Tewari |
| Online Normalization for Training Neural Networks | Vitaliy Chiley · Ilya Sharapov · Atli Kosson · Urs Koster · Ryan Reece · Sofia Samaniego de la Fuente · Vishal Subbiah · Michael James |
| Online Prediction of Switching Graph Labelings with Cluster Specialists | Mark Herbster · James Robinson |
| Secretary Ranking with Minimal Inversions | Sepehr Assadi · Eric Balkanski · Renato Leme |
| Dying Experts: Efficient Algorithms with Optimal Regret Bounds | Hamid Shayestehmanesh · Sajjad Azami · Nishant Mehta |
| Dynamic Local Regret for Non-convex Online Forecasting | Sergul Aydore · Tianhao Zhu · Dean Foster |
| Online Convex Matrix Factorization with Representative Regions | Jianhao Peng · Olgica Milenkovic · Abhishek Agarwal |
| Online Forecasting of Total-Variation-bounded Sequences | Dheeraj Baby · Yu-Xiang Wang |
| Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function | Aviv Rosenberg · Yishay Mansour |
| Private Learning Implies Online Learning: An Efficient Reduction | Alon Gonen · Elad Hazan · Shay Moran |
| Random Path Selection for Continual Learning | Jathushan Rajasegaran · Munawar Hayat · Salman H Khan · Fahad Shahbaz Khan · Ling Shao |
| Superposition of many models into one | Brian Cheung · Alexander Terekhov · Yubei Chen · Pulkit Agrawal · Bruno Olshausen |
| User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning | Dirk van der Hoeven |