ICLR Poster Efficient Reinforcement Learning in Factored MDPs ...
Track: Poster Session 7 - ICLR 2025
In recent years, implicit deep learning has emerged as a method to increase the depth of deep neural networks. While their training is memory-efficient, they ...
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs · How ... Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning ...
12:30 a.m.. Coffee Break. 1 a.m.. Oral 1 Track 4: Social Aspects of Machine Learning [1:00- ...
Track: Poster Session 6 - ICLR 2025
Within SYMBOL, we then develop three distinct strategies based on reinforcement learning, so as to meta-learn the SEG efficiently. Extensive ...
Effective out-of-distribution (OOD) detection is crucial for reliable machine learning models, yet most current methods are limited in practical ...
Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs ... Pre-Training Goal-based Models for Sample-Efficient Reinforcement Learning · A ...
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes · PGrad: Learning ...
Track: Poster Session 7 - ICLR 2025
... efficient visual reinforcement learning (VRL). Although methods like ... factor models, Gaussian mixture models, and contrastive learning.
Track: Poster Session 1 - ICLR 2025
... MDP using video ... learning and classic heuristics to achieve efficient presolving adjusting, avoiding tedious reinforcement learning.
Track: Poster Session 5 - ICLR 2025
Recent works have shown that language modeling can be effectively used to train reinforcement learning (RL) policies. However, the success of applying ...
Track: Poster Session 8 - ICLR 2025
Offline reinforcement learning (RL) allows agents to learn effective, return-maximizing policies from a static dataset. Three popular algorithms ...
Track: Poster Session 3 - ICLR 2025
Machine learning potentials have previously shown great success in this domain, reaching increasingly better accuracy while maintaining computational efficiency ...
Track: Poster Session 2 - ICLR 2025
... (MDP) setup differs. We point out that its data-unobserved setup ... Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier.
Track: Poster Session 11 - ICLR 2025
Extensive experimental results on multiple reinforcement learning tasks demonstrate the efficiency of our new algorithms. Maximum Entropy RL (Provably) ...
Poster Session 08 [9:00-11:00] · Anytime Sampling for Autoregressive ... Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL.
Track: Poster Session 6 - ICLR
In this paper, we propose TAPEX to show that table pre-training can be achieved by learning a neural SQL executor over a synthetic corpus, which is obtained by ...
Track: Poster Session 2 - ICLR 2025
Distributional Reinforcement Learning (RL) differs from traditional RL by estimating the distribution over returns to capture the intrinsic uncertainty of MDPs.
Track: Poster Session 5 - ICLR 2025
When the available hardware cannot meet the memory and compute requirements to efficiently train high performing machine learning models, a compromise in either ...
Track: Poster Session 12 - ICLR 2025
Reinforcement learning encounters many challenges when applied directly in the real world. Sim-to-real transfer is widely used to transfer the knowledge learned ...
Track: Poster Session 9 - ICLR 2025
Human intervention is an effective way to inject human knowledge into the training loop of reinforcement learning, which can bring fast learning and ensured ...