284 citations
- Centre National de la Recherche ScientifiqueFR17 papers
- Western Digital (United States)US15 papers
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11 papers · 1 filter
Latent-Conditioned Policy Gradient for Multi-Objective Deep Reinforcement Learning
Takuya Kanazawa, Chetan Gupta
Sequential decision making in the real world often requires finding a good balance of conflicting objectives. In general, there exist a plethora of Pareto-optimal policies that emb…
A Functional approach for Two Way Dimension Reduction in Time Series
Aniruddha Rajendra Rao, Haiyan Wang, Chetan Gupta
The rise in data has led to the need for dimension reduction techniques, especially in the area of non-scalar variables, including time series, natural language processing, and com…
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network
Takuya Kanazawa, Chetan Gupta
Development of an accurate, flexible, and numerically efficient uncertainty quantification (UQ) method is one of fundamental challenges in machine learning. Previously, a UQ method…
Distributional Actor-Critic Ensemble for Uncertainty-Aware Continuous Control
Takuya Kanazawa, Haiyan Wang, Chetan Gupta
Uncertainty quantification is one of the central challenges for machine learning in real-world applications. In reinforcement learning, an agent confronts two kinds of uncertainty,…
One-parameter family of acquisition functions for efficient global optimization
Takuya Kanazawa
Bayesian optimization (BO) with Gaussian processes is a powerful methodology to optimize an expensive black-box function with as few function evaluations as possible. The expected…
Deep Time Series Models for Scarce Data
Qiyao Wang, Ahmed Farahat, Chetan Gupta +1
Time series data have grown at an explosive rate in numerous domains and have stimulated a surge of time series modeling research. A comprehensive comparison of different time seri…