Papers
Modeling Dynamic Missingness of Implicit Feedback for Recommendation
Menghan Wang, Mingming Gong, Xiaolin Zheng et al.
Chaining Mutual Information and Tightening Generalization Bounds
Amir Asadi, Emmanuel Abbe, Sergio Verdu
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen Li, Qifeng Chen, Vladlen Koltun
Boosted Sparse and Low-Rank Tensor Regression
Lifang He, Kun Chen, Wanwan Xu et al.
Causal Discovery from Discrete Data using Hidden Compact Representation
Ruichu Cai, Jie Qiao, Kun Zhang et al.
Constructing Unrestricted Adversarial Examples with Generative Models
Yang Song, Rui Shu, Nate Kushman et al.
Rectangular Bounding Process
Xuhui Fan, Bin Li, Scott SIsson
Reward learning from human preferences and demonstrations in Atari
Borja Ibarz, Jan Leike, Tobias Pohlen et al.
Geometry-Aware Recurrent Neural Networks for Active Visual Recognition
Ricson Cheng, Ziyan Wang, Katerina Fragkiadaki
Stochastic Composite Mirror Descent: Optimal Bounds with High Probabilities
Yunwen Lei, Ke Tang
A Neural Compositional Paradigm for Image Captioning
Bo Dai, Sanja Fidler, Dahua Lin
Multi-armed Bandits with Compensation
Siwei Wang, Longbo Huang
Estimating Learnability in the Sublinear Data Regime
Weihao Kong, Gregory Valiant
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models
Chen Dan, Liu Leqi, Bryon Aragam et al.
A no-regret generalization of hierarchical softmax to extreme multi-label classification
Marek Wydmuch, Kalina Jasinska, Mikhail Kuznetsov et al.
Hybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation
JING LI, Rafal Mantiuk, Junle Wang et al.
Learning to Optimize Tensor Programs
Tianqi Chen, Lianmin Zheng, Eddie Yan et al.
Learning Confidence Sets using Support Vector Machines
Wenbo Wang, Xingye Qiao
ℓ_1-regression with Heavy-tailed Distributions
Lijun Zhang, Zhi-Hua Zhou
Watch Your Step: Learning Node Embeddings via Graph Attention
Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou et al.
Representer Point Selection for Explaining Deep Neural Networks
Chih-Kuan Yeh, Joon Kim, Ian En-Hsu Yen et al.
Online Robust Policy Learning in the Presence of Unknown Adversaries
Aaron Havens, Zhanhong Jiang, Soumik Sarkar
BourGAN: Generative Networks with Metric Embeddings
Chang Xiao, Peilin Zhong, Changxi Zheng
Model-based targeted dimensionality reduction for neuronal population data
Mikio Aoi, Jonathan W Pillow
Stochastic Chebyshev Gradient Descent for Spectral Optimization
Insu Han, Haim Avron, Jinwoo Shin