65 citations · 78 across the 3 of their papers we have counts for
4 papers · 1 filter
Intrinsic Reward Driven Imitation Learning via Generative Model
Xingrui Yu, Yueming Lyu, Ivor W. Tsang
Imitation learning in a high-dimensional environment is challenging. Most inverse reinforcement learning (IRL) methods fail to outperform the demonstrator in such a high-dimensiona…
Black-box Optimizer with Implicit Natural Gradient
Yueming Lyu, Ivor W. Tsang
Black-box optimization is primarily important for many compute-intensive applications, including reinforcement learning (RL), robot control, etc. This paper presents a novel theore…
Curriculum Loss: Robust Learning and Generalization against Label Corruption
Yueming Lyu, Ivor W. Tsang
Deep neural networks (DNNs) have great expressive power, which can even memorize samples with wrong labels. It is vitally important to reiterate robustness and generalization in DN…
Efficient Batch Black-box Optimization with Deterministic Regret Bounds
Yueming Lyu, Yuan Yuan, Ivor W. Tsang
In this work, we investigate black-box optimization from the perspective of frequentist kernel methods. We propose a novel batch optimization algorithm, which jointly maximizes the…