- Aakarsh Malhotra, Mayank Vatsa, Richa Singh 0001. Dropped Scheduled Task: Mitigating Negative Transfer in Multi-task Learning using Dynamic Task Dropping. Trans. Mach. Learn. Res., 2023, 2023.
- Kiri L. Wagstaff, Thomas G. Dietterich. Hidden Heterogeneity: When to Choose Similarity-Based Calibration. Trans. Mach. Learn. Res., 2023, 2023.
- Vijaya Raghavan T. Ramkumar, Elahe Arani, Bahram Zonooz. Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks. Trans. Mach. Learn. Res., 2023, 2023.
- Kiarash Banihashem, Adish Singla, Goran Radanovic. Defense Against Reward Poisoning Attacks in Reinforcement Learning. Trans. Mach. Learn. Res., 2023, 2023.
- Asher Trockman, J. Zico Kolter. Patches Are All You Need?. Trans. Mach. Learn. Res., 2023, 2023.
- Patrick M. Soga, David Chiang 0001. Bridging Graph Position Encodings for Transformers with Weighted Graph-Walking Automata. Trans. Mach. Learn. Res., 2023, 2023.
- Shagun Sodhani, Sergey Levine, Amy Zhang 0001. Improving Generalization with Approximate Factored Value Functions. Trans. Mach. Learn. Res., 2023, 2023.
- Guanlin Liu, Lifeng Lai. Action Poisoning Attacks on Linear Contextual Bandits. Trans. Mach. Learn. Res., 2023, 2023.
- Javier Burroni, Kenta Takatsu, Justin Domke, Daniel Sheldon. U-Statistics for Importance-Weighted Variational Inference. Trans. Mach. Learn. Res., 2023, 2023.
- Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister. SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res., 2023, 2023.