Papers
Sparse PCA from Sparse Linear Regression
Guy Bresler, Sung Min Park, Madalina Persu
Learning Task Specifications from Demonstrations
Marcell Vazquez-Chanlatte, Susmit Jha, Ashish Tiwari et al.
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
Bart van Merrienboer, Dan Moldovan, Alexander Wiltschko
Variational Bayesian Monte Carlo
Luigi Acerbi
Transfer of Deep Reactive Policies for MDP Planning
Aniket (Nick) Bajpai, Sankalp Garg, Mausam
Boosting Black Box Variational Inference
Francesco Locatello, Gideon Dresdner, Rajiv Khanna et al.
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability
Michael Tsang, Hanpeng Liu, Sanjay Purushotham et al.
Boolean Decision Rules via Column Generation
Sanjeeb Dash, Oktay Gunluk, Dennis Wei
Learning with SGD and Random Features
Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects
Adam Kosiorek, Hyunjik Kim, Yee Whye Teh et al.
Causal Inference via Kernel Deviance Measures
Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh
VideoCapsuleNet: A Simplified Network for Action Detection
Kevin Duarte, Yogesh Rawat, Mubarak Shah
Learning Latent Subspaces in Variational Autoencoders
Jack Klys, Jake Snell, Richard Zemel
Improving Online Algorithms via ML Predictions
Manish Purohit, Zoya Svitkina, Ravi Kumar
BRITS: Bidirectional Recurrent Imputation for Time Series
Wei Cao, Dong Wang, Jian Li et al.
Overlapping Clustering Models, and One (class) SVM to Bind Them All
Xueyu Mao, Purnamrita Sarkar, Deepayan Chakrabarti
Supervising Unsupervised Learning
Vikas Garg, Adam T Kalai
Hybrid Knowledge Routed Modules for Large-scale Object Detection
ChenHan Jiang, Hang Xu, Xiaodan Liang et al.
Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces
Motoya Ohnishi, Masahiro Yukawa, Mikael Johansson et al.
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization
Bargav Jayaraman, Lingxiao Wang, David Evans et al.
Learning to Play With Intrinsically-Motivated, Self-Aware Agents
Nick Haber, Damian Mrowca, Stephanie Wang et al.
Deep Reinforcement Learning of Marked Temporal Point Processes
Utkarsh Upadhyay, Abir De, Manuel Gomez Rodriguez
To Trust Or Not To Trust A Classifier
Heinrich Jiang, Been Kim, Melody Guan et al.
Adversarial Multiple Source Domain Adaptation
Han Zhao, Shanghang Zhang, Guanhang Wu et al.
Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions
Mingrui Liu, Xiaoxuan Zhang, Lijun Zhang et al.