996 citations · 1.7k across the 31 of their papers we have counts for
6 papers · 1 filter
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning
Deheng Ye, Zhao Liu, Mingfei Sun +15
We study the reinforcement learning problem of complex action control in the Multi-player Online Battle Arena (MOBA) 1v1 games. This problem involves far more complicated state and…
Large Scale Open-Set Deep Logo Detection
Muhammet Bastan, Hao-Yu Wu, Tian Cao +2
We present an open-set logo detection (OSLD) system, which can detect (localize and recognize) any number of unseen logo classes without re-training; it only requires a small set o…
Amortized Population Gibbs Samplers with Neural Sufficient Statistics
Hao Wu, Heiko Zimmermann, Eli Sennesh +2
We develop amortized population Gibbs (APG) samplers, a class of scalable methods that frames structured variational inference as adaptive importance sampling. APG samplers constru…
A Variational Approach for Learning from Positive and Unlabeled Data
Hui Chen, Fangqing Liu, Yin Wang +2
Learning binary classifiers only from positive and unlabeled (PU) data is an important and challenging task in many real-world applications, including web text classification, dise…
Adaptive Learning Material Recommendation in Online Language Education
Shuhan Wang, Hao Wu, Ji Hun Kim +1
Recommending personalized learning materials for online language learning is challenging because we typically lack data about the student's ability and the relative difficulty of l…
UniVSE: Robust Visual Semantic Embeddings via Structured Semantic Representations
Hao Wu, Jiayuan Mao, Yufeng Zhang +4
We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a joint space of visual and textual concepts. The space unifies the concepts at different levels, including obje…