Deep RL

Papers about distributed deep and reinforcement learning.

[Deep RL @deep_rl]

Sequence-to-Sequence Forecasting-aided State Estimation for Power
Systems - Kamal Basulaiman https://t.co/O0SDebkSTd

[Deep RL @deep_rl]

Learning to detect an animal sound from five examples - Inês Nolasco https://t.co/fUAEOgVnlU

[Deep RL @deep_rl]

Know your Enemy: Investigating Monte-Carlo Tree Search with Opponent
Models in Pommerman - Jannis Weil https://t.co/DSuy2Ew8DI

[Deep RL @deep_rl]

U-DiT TTS: U-Diffusion Vision Transformer for Text-to-Speech - Xin Jing https://t.co/x9U9J7KmVa

[Deep RL @deep_rl]

Regularization and Variance-Weighted Regression Achieves Minimax
Optimality in Linear MDPs: Theory and Practice - Toshinori Kitamura https://t.co/oo6gdxcGUK

[Deep RL @deep_rl]

Editing Large Language Models: Problems, Methods, and Opportunities - Yunzhi Yao https://t.co/yIUXFc71yK

[Deep RL @deep_rl]

Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained
Features Model - Peter Súkeník https://t.co/Nt00kGw2gt

[Deep RL @deep_rl]

INVICTUS: Optimizing Boolean Logic Circuit Synthesis via Synergistic
Learning and Search - Animesh Basak Chowdhury https://t.co/1MPCDqQXy8

[Deep RL @deep_rl]

Scaling Serverless Functions in Edge Networks: A Reinforcement Learning
Approach - Mounir Bensalem https://t.co/pUOAOrkcBm

[Deep RL @deep_rl]

Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition
using Wrist-worn Inertial Sensors - Alexander Hoelzemann https://t.co/sUJHkScJza

[Deep RL @deep_rl]

Policy Representation via Diffusion Probability Model for Reinforcement
Learning - Long Yang https://t.co/PP2YL3r6Cs

[Deep RL @deep_rl]

Debiased Automatic Speech Recognition for Dysarthric Speech via Sample
Reweighting with Sample Affinity Test - Eungbeom Kim https://t.co/QUKGUMh7GG

[Deep RL @deep_rl]

Restore Anything Pipeline: Segment Anything Meets Image Restoration - Jiaxi Jiang https://t.co/oAJIvqXgKn

[Deep RL @deep_rl]

Breaking the Paradox of Explainable Deep Learning - Arlind Kadra https://t.co/DzHyr0RTl4

[Deep RL @deep_rl]

Hierarchical Partitioning Forecaster - Christopher Mattern https://t.co/8cGSIovcm1

[Deep RL @deep_rl]

Road Planning for Slums via Deep Reinforcement Learning - Yu Zheng https://t.co/wz8UOK99J2

[Deep RL @deep_rl]

Federated Learning of Medical Concepts Embedding using BEHRT - Ofir Ben Shoham https://t.co/zL4mOZvbAB

[Deep RL @deep_rl]

POEM: Polarization of Embeddings for Domain-Invariant Representations - Sang-Yeong Jo https://t.co/Sm13EFFEb0

[Deep RL @deep_rl]

Distributed Learning over Networks with Graph-Attention-Based
Personalization - Zhuojun Tian https://t.co/8xs1tWbrA6

[Deep RL @deep_rl]

Towards generalizing deep-audio fake detection networks - Konstantin Gasenzer https://t.co/y8bkEFSu58