Saved in:
| Main Authors: | Vijesh, Antony, R, Shreyas S |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.02369 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Multi-Step Minimax Q-learning Algorithm for Two-Player Zero-Sum Markov Games
by: R, Shreyas S, et al.
Published: (2024)
by: R, Shreyas S, et al.
Published: (2024)
Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning
by: R, Shreyas S
Published: (2024)
by: R, Shreyas S
Published: (2024)
One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learning
by: Nguyen, Thanh, et al.
Published: (2025)
by: Nguyen, Thanh, et al.
Published: (2025)
Implicit Q-Learning and SARSA: Liberating Policy Control from Step-Size Calibration
by: Kim, Hwanwoo, et al.
Published: (2026)
by: Kim, Hwanwoo, et al.
Published: (2026)
Leverage-Weighted Conformal Prediction
by: Fadnavis, Shreyas
Published: (2026)
by: Fadnavis, Shreyas
Published: (2026)
One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow
by: Wang, Zeyuan, et al.
Published: (2025)
by: Wang, Zeyuan, et al.
Published: (2025)
Iterated $Q$-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning
by: Vincent, Théo, et al.
Published: (2024)
by: Vincent, Théo, et al.
Published: (2024)
Neuroscience-Inspired Memory Replay for Continual Learning: A Comparative Study of Predictive Coding and Backpropagation-Based Strategies
by: Nalagatla, Goutham, et al.
Published: (2025)
by: Nalagatla, Goutham, et al.
Published: (2025)
Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent
by: Moniri, Behrad, et al.
Published: (2026)
by: Moniri, Behrad, et al.
Published: (2026)
Predicting ATP binding sites in protein sequences using Deep Learning and Natural Language Processing
by: V, Shreyas, et al.
Published: (2024)
by: V, Shreyas, et al.
Published: (2024)
The Pursuit of Diversity: Multi-Objective Testing of Deep Reinforcement Learning Agents
by: Bartlett, Antony, et al.
Published: (2025)
by: Bartlett, Antony, et al.
Published: (2025)
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
by: Dandi, Yatin, et al.
Published: (2023)
by: Dandi, Yatin, et al.
Published: (2023)
Two-Step Offline Preference-Based Reinforcement Learning with Constrained Actions
by: Xu, Yinglun, et al.
Published: (2023)
by: Xu, Yinglun, et al.
Published: (2023)
GradNetOT: Learning Optimal Transport Maps with GradNets
by: Chaudhari, Shreyas, et al.
Published: (2025)
by: Chaudhari, Shreyas, et al.
Published: (2025)
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation
by: Pham, Dzung, et al.
Published: (2023)
by: Pham, Dzung, et al.
Published: (2023)
Spatiotemporal Wildfire Prediction and Reinforcement Learning for Helitack Suppression
by: Mathur, Shaurya, et al.
Published: (2026)
by: Mathur, Shaurya, et al.
Published: (2026)
FedFitTech: A Baseline in Federated Learning for Fitness Tracking
by: Oz, Zeyneddin, et al.
Published: (2025)
by: Oz, Zeyneddin, et al.
Published: (2025)
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
by: Moniri, Behrad, et al.
Published: (2023)
by: Moniri, Behrad, et al.
Published: (2023)
Learning from Label Proportions and Covariate-shifted Instances
by: Singh, Sagalpreet, et al.
Published: (2024)
by: Singh, Sagalpreet, et al.
Published: (2024)
Quantile Q-Learning: Revisiting Offline Extreme Q-Learning with Quantile Regression
by: Gao, Xinming, et al.
Published: (2025)
by: Gao, Xinming, et al.
Published: (2025)
Classification with a Network of Partially Informative Agents: Enabling Wise Crowds from Individually Myopic Classifiers
by: Yao, Tong, et al.
Published: (2024)
by: Yao, Tong, et al.
Published: (2024)
MonoCon: A general framework for learning ultra-compact high-fidelity representations using monotonicity constraints
by: Gokhale, Shreyas
Published: (2025)
by: Gokhale, Shreyas
Published: (2025)
Learning Dynamical Systems by Leveraging Data from Similar Systems
by: Xin, Lei, et al.
Published: (2023)
by: Xin, Lei, et al.
Published: (2023)
Reward Fine-Tuning Two-Step Diffusion Models via Learning Differentiable Latent-Space Surrogate Reward
by: Jia, Zhiwei, et al.
Published: (2024)
by: Jia, Zhiwei, et al.
Published: (2024)
Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
by: Pang, Tianyu, et al.
Published: (2026)
by: Pang, Tianyu, et al.
Published: (2026)
STARLING: Self-supervised Training of Text-based Reinforcement Learning Agent with Large Language Models
by: Basavatia, Shreyas, et al.
Published: (2024)
by: Basavatia, Shreyas, et al.
Published: (2024)
Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence
by: Yongacoglu, Bora, et al.
Published: (2023)
by: Yongacoglu, Bora, et al.
Published: (2023)
ReLU Networks as Random Functions: Their Distribution in Probability Space
by: Chaudhari, Shreyas, et al.
Published: (2025)
by: Chaudhari, Shreyas, et al.
Published: (2025)
Strategically Conservative Q-Learning
by: Shimizu, Yutaka, et al.
Published: (2024)
by: Shimizu, Yutaka, et al.
Published: (2024)
Q&A Label Learning
by: Kawamoto, Kota, et al.
Published: (2023)
by: Kawamoto, Kota, et al.
Published: (2023)
Moment Matching Q-Learning
by: Yiyan, et al.
Published: (2026)
by: Yiyan, et al.
Published: (2026)
SSL-SE-EEG: A Framework for Robust Learning from Unlabeled EEG Data with Self-Supervised Learning and Squeeze-Excitation Networks
by: Chowdhury, Meghna Roy, et al.
Published: (2025)
by: Chowdhury, Meghna Roy, et al.
Published: (2025)
Inverse Q-Learning Done Right: Offline Imitation Learning in $Q^π$-Realizable MDPs
by: Moulin, Antoine, et al.
Published: (2025)
by: Moulin, Antoine, et al.
Published: (2025)
$S^3$-R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data
by: Goel, Harsh, et al.
Published: (2026)
by: Goel, Harsh, et al.
Published: (2026)
Laplace Learning in Wasserstein Space
by: Oliver, Mary Chriselda Antony, et al.
Published: (2025)
by: Oliver, Mary Chriselda Antony, et al.
Published: (2025)
Hybrid SARIMA LSTM Model for Local Weather Forecasting: A Residual Learning Approach for Data Driven Meteorological Prediction
by: Rajeev, Shreyas, et al.
Published: (2026)
by: Rajeev, Shreyas, et al.
Published: (2026)
Digi-Q: Learning Q-Value Functions for Training Device-Control Agents
by: Bai, Hao, et al.
Published: (2025)
by: Bai, Hao, et al.
Published: (2025)
Few-Shot Concept Unlearning with Low Rank Adaptation
by: Shreyas, Udaya, et al.
Published: (2025)
by: Shreyas, Udaya, et al.
Published: (2025)
Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis
by: Chung, Long Kiu, et al.
Published: (2025)
by: Chung, Long Kiu, et al.
Published: (2025)
Deep SOR Minimax Q-learning for Two-player Zero-sum Game
by: Gautam, Saksham, et al.
Published: (2025)
by: Gautam, Saksham, et al.
Published: (2025)
Similar Items
-
A Multi-Step Minimax Q-learning Algorithm for Two-Player Zero-Sum Markov Games
by: R, Shreyas S, et al.
Published: (2024) -
Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning
by: R, Shreyas S
Published: (2024) -
One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learning
by: Nguyen, Thanh, et al.
Published: (2025) -
Implicit Q-Learning and SARSA: Liberating Policy Control from Step-Size Calibration
by: Kim, Hwanwoo, et al.
Published: (2026) -
Leverage-Weighted Conformal Prediction
by: Fadnavis, Shreyas
Published: (2026)