Gal Dalal

According to our database1, Gal Dalal authored at least 33 papers between 2015 and 2024.

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Bibliography

2024
Gradient Boosting Reinforcement Learning.
CoRR, 2024

PlaMo: Plan and Move in Rich 3D Physical Environments.
CoRR, 2024

Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tree Search-Based Policy Optimization under Stochastic Execution Delay.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
On the Products of Stochastic and Diagonal Matrices.
CoRR, 2023

SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search.
CoRR, 2023

AutoScratch: ML-Optimized Cache Management for Inference-Oriented GPUs.
Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

Planning and Learning with Adaptive Lookahead.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Reinforcement Learning for Datacenter Congestion Control.
SIGMETRICS Perform. Evaluation Rev., 2022

SoftTreeMax: Policy Gradient with Tree Search.
CoRR, 2022

Reinforcement Learning with a Terminator.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Acting in Delayed Environments with Non-Stationary Markov Policies.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
The Architectural Implications of Distributed Reinforcement Learning on CPU-GPU Systems.
CoRR, 2020

A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
How to Combine Tree-Search Methods in Reinforcement Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Multiple-Step Greedy Policies in Online and Approximate Reinforcement Learning.
CoRR, 2018

Safe Exploration in Continuous Action Spaces.
CoRR, 2018

Chance-Constrained Outage Scheduling using a Machine Learning Proxy.
CoRR, 2018

Multiple-Step Greedy Policies in Approximate and Online Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Beyond the One-Step Greedy Approach in Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Finite Sample Analysis of Two-Timescale Stochastic Approximation with Applications to Reinforcement Learning.
Proceedings of the Conference On Learning Theory, 2018

Finite Sample Analyses for TD(0) With Function Approximation.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Finite Sample Analysis for TD(0) with Linear Function Approximation.
CoRR, 2017

Concentration Bounds for Two Timescale Stochastic Approximation with Applications to Reinforcement Learning.
CoRR, 2017

Supervised learning for optimal power flow as a real-time proxy.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2017

Anomaly Detection in Large Databases Using Behavioral Patterning.
Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

2016
Unit Commitment using Nearest Neighbor as a Short-Term Proxy.
CoRR, 2016

Distributed scenario-based optimization for asset management in a hierarchical decision making environment.
Proceedings of the Power Systems Computation Conference, 2016

Hierarchical Decision Making In Electricity Grid Management.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Reinforcement Learning for the Unit Commitment Problem.
CoRR, 2015


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