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06/15/2021
Thompson Sampling for Unimodal Bandits
In this paper, we propose a Thompson Sampling algorithm for unimodal ban...
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04/22/2021
Optimize Neural Fictitious Self-Play in Regret Minimization Thinking
Optimization of deep learning algorithms to approach Nash Equilibrium re...
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04/16/2021
Sync-Switch: Hybrid Parameter Synchronization for Distributed Deep Learning
Stochastic Gradient Descent (SGD) has become the de facto way to train d...
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04/07/2020
Characterizing and Modeling Distributed Training with Transient Cloud GPU Servers
Cloud GPU servers have become the de facto way for deep learning practit...
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12/05/2019
Perseus: Characterizing Performance and Cost of Multi-Tenant Serving for CNN Models
Deep learning models are increasingly used for end-user applications, su...
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07/31/2019
Inverse Reinforcement Learning with Multiple Ranked Experts
We consider the problem of learning to behave optimally in a Markov Deci...
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07/01/2019
FiDi-RL: Incorporating Deep Reinforcement Learning with Finite-Difference Policy Search for Efficient Learning of Continuous Control
In recent years significant progress has been made in dealing with chall...
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05/17/2019
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning
Off-policy reinforcement learning with eligibility traces is challenging...
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03/22/2019
Monte Carlo Neural Fictitious Self-Play: Achieve Approximate Nash equilibrium of Imperfect-Information Games
Researchers on artificial intelligence have achieved human-level intelli...
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03/22/2019
Monte Carlo Neural Fictitious Self-Play: Approach to Approximate Nash equilibrium of Imperfect-Information Games
Researchers on artificial intelligence have achieved human-level intelli...
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02/28/2019
Speeding up Deep Learning with Transient Servers
Distributed training frameworks, like TensorFlow, have been proposed as ...
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02/25/2019
Field-aware Neural Factorization Machine for Click-Through Rate Prediction
Recommendation systems and computing advertisements have gradually enter...
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02/21/2018
