Papers
Deep Anomaly Detection Using Geometric Transformations
Izhak Golan, Ran El-Yaniv
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding
Kexin Yi, Jiajun Wu, Chuang Gan et al.
GLoMo: Unsupervised Learning of Transferable Relational Graphs
Zhilin Yang, Jake Zhao, Bhuwan Dhingra et al.
Learning Temporal Point Processes via Reinforcement Learning
Shuang Li, Shuai Xiao, Shixiang Zhu et al.
Deep State Space Models for Time Series Forecasting
Syama Sundar Rangapuram, Matthias W Seeger, Jan Gasthaus et al.
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
Nima Anari, Constantinos Daskalakis, Wolfgang Maass et al.
Distributed Stochastic Optimization via Adaptive SGD
Ashok Cutkosky, Róbert Busa-Fekete
Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making
Nishant Desai, Andrew Critch, Stuart Russell
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss
Stephen Mussmann, Percy Liang
On the Convergence and Robustness of Training GANs with Regularized Optimal Transport
Maziar Sanjabi, Jimmy Ba, Meisam Razaviyayn et al.
Randomized Prior Functions for Deep Reinforcement Learning
Ian Osband, John Aslanides, Albin Cassirer
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
Arthur Jacot, Franck Gabriel, Clement Hongler
Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization
Hoi-To Wai, Zhuoran Yang, Zhaoran Wang et al.
Sequence-to-Segment Networks for Segment Detection
Zijun Wei, Boyu Wang, Minh Hoai Nguyen et al.
Posterior Concentration for Sparse Deep Learning
Nicholas G Polson, Veronika Ročková
Uniform Convergence of Gradients for Non-Convex Learning and Optimization
Dylan J Foster, Ayush Sekhari, Karthik Sridharan
An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression
Sheng Chen, Arindam Banerjee
Quadratic Decomposable Submodular Function Minimization
Pan Li, Niao He, Olgica Milenkovic
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC
Tolga Birdal, Umut Simsekli, Mustafa Onur Eken et al.
Bayesian Adversarial Learning
Nanyang Ye, Zhanxing Zhu
Meta-Learning MCMC Proposals
Tongzhou Wang, YI WU, Dave Moore et al.
LinkNet: Relational Embedding for Scene Graph
Sanghyun Woo, Dahun Kim, Donghyeon Cho et al.
Optimal Subsampling with Influence Functions
Daniel Ting, Eric Brochu
SING: Symbol-to-Instrument Neural Generator
Alexandre Defossez, Neil Zeghidour, Nicolas Usunier et al.