Papers
Learning to Decompose and Disentangle Representations for Video Prediction
Jun-Ting Hsieh, Bingbin Liu, De-An Huang et al.
Teaching Inverse Reinforcement Learners via Features and Demonstrations
Luis Haug, Sebastian Tschiatschek, Adish Singla
Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions
Minhyuk Sung, Hao Su, Ronald Yu et al.
Reducing Network Agnostophobia
Akshay Raj Dhamija, Manuel Günther, Terrance Boult
Toddler-Inspired Visual Object Learning
Sven Bambach, David Crandall, Linda Smith et al.
3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Maurice Weiler, Mario Geiger, Max Welling et al.
Robust Learning of Fixed-Structure Bayesian Networks
Yu Cheng, Ilias Diakonikolas, Daniel Kane et al.
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
A convex program for bilinear inversion of sparse vectors
Alireza Aghasi, Ali Ahmed, Paul Hand et al.
Fast Approximate Natural Gradient Descent in a Kronecker Factored Eigenbasis
Thomas George, César Laurent, Xavier Bouthillier et al.
Bandit Learning in Concave N-Person Games
Mario Bravo, David Leslie, Panayotis Mertikopoulos
A Probabilistic U-Net for Segmentation of Ambiguous Images
Simon Kohl, Bernardino Romera-Paredes, Clemens Meyer et al.
Designing by Training: Acceleration Neural Network for Fast High-Dimensional Convolution
Longquan Dai, Liang Tang, Yuan Xie et al.
But How Does It Work in Theory? Linear SVM with Random Features
Yitong Sun, Anna Gilbert, Ambuj Tewari
Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch
Osman Asif Malik, Stephen Becker
Neural Voice Cloning with a Few Samples
Sercan Arik, Jitong Chen, Kainan Peng et al.
Communication Compression for Decentralized Training
Hanlin Tang, Shaoduo Gan, Ce Zhang et al.
Direct Runge-Kutta Discretization Achieves Acceleration
Jingzhao Zhang, Aryan Mokhtari, Suvrit Sra et al.
Learning to Exploit Stability for 3D Scene Parsing
Yilun Du, Zhijian Liu, Hector Basevi et al.
Multi-Task Learning as Multi-Objective Optimization
Ozan Sener, Vladlen Koltun
Collaborative Learning for Deep Neural Networks
Guocong Song, Wei Chai
Large Margin Deep Networks for Classification
Gamaleldin Elsayed, Dilip Krishnan, Hossein Mobahi et al.
Fully Neural Network Based Speech Recognition on Mobile and Embedded Devices
Jinhwan Park, Yoonho Boo, Iksoo Choi et al.
Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Zi Wang, Beomjoon Kim, Leslie Pack Kaelbling
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes