112 citations · 193 across the 26 of their papers we have counts for
4 papers · 1 filter
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…
Marginalized Average Attentional Network for Weakly-Supervised Learning
Yuan Yuan, Yueming Lyu, Xi Shen +2
In weakly-supervised temporal action localization, previous works have failed to locate dense and integral regions for each entire action due to the overestimation of the most sali…
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…