Papers
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Carlos Villacampa-Calvo, Daniel Hernández-Lobato
Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
Weizhong Zhang, Bin Hong, Wei Liu et al.
Schema Networks: Zero-shot Transfer with a Generative Causal Model of Intuitive Physics
Ken Kansky, Tom Silver, David A. Mély et al.
Second-Order Kernel Online Convex Optimization with Adaptive Sketching
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Selective Inference for Sparse High-Order Interaction Models
Shinya Suzumura, Kazuya Nakagawa, Yuta Umezu et al.
Self-Paced Co-training
Fan Ma, Deyu Meng, Qi Xie et al.
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data
Tomoya Sakai, Marthinus Christoffel Plessis, Gang Niu et al.
Sequence Modeling via Segmentations
Chong Wang, Yining Wang, Po-Sen Huang et al.
Sequence to Better Sequence: Continuous Revision of Combinatorial Structures
Jonas Mueller, David Gifford, Tommi Jaakkola
Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control
Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau et al.
Sharp Minima Can Generalize For Deep Nets
Laurent Dinh, Razvan Pascanu, Samy Bengio et al.
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation
Yacine Jernite, Anna Choromanska, David Sontag
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang, Alex Gittens, Michael W. Mahoney
Sliced Wasserstein Kernel for Persistence Diagrams
Mathieu Carrière, Marco Cuturi, Steve Oudot
Soft-DTW: a Differentiable Loss Function for Time-Series
Marco Cuturi, Mathieu Blondel
Source-Target Similarity Modelings for Multi-Source Transfer Gaussian Process Regression
Pengfei Wei, Ramon Sagarna, Yiping Ke et al.
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang, Aurélie C. Lozano
Spectral Learning from a Single Trajectory under Finite-State Policies
Borja Balle, Odalric-Ambrym Maillard
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling
Jun-ichiro Hirayama, Aapo Hyvärinen, Motoaki Kawanabe
SplitNet: Learning to Semantically Split Deep Networks for Parameter Reduction and Model Parallelization
Juyong Kim, Yookoon Park, Gunhee Kim et al.
Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
Jakob Foerster, Nantas Nardelli, Gregory Farquhar et al.
State-Frequency Memory Recurrent Neural Networks
Hao Hu, Guo-Jun Qi
Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent Coarsening
Mohsen Ahmadi Fahandar, Eyke Hüllermeier, Inés Couso
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent
Tyler B. Johnson, Carlos Guestrin