Papers
Hidden Technical Debt in Machine Learning Systems
D. Sculley, Gary Holt, Daniel Golovin et al.
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Cengiz Pehlevan, Dmitri Chklovskii
Consistent Multilabel Classification
Oluwasanmi O Koyejo, Nagarajan Natarajan, Pradeep K Ravikumar et al.
On the Optimality of Classifier Chain for Multi-label Classification
Weiwei Liu, Ivor Tsang
Linear Multi-Resource Allocation with Semi-Bandit Feedback
Tor Lattimore, Koby Crammer, Csaba Szepesvari
Structured Transforms for Small-Footprint Deep Learning
Vikas Sindhwani, Tara Sainath, Sanjiv Kumar
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation
Jaya Kawale, Hung H Bui, Branislav Kveton et al.
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching
Xiao Li, Kannan Ramchandran
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
Jonas W Mueller, Tommi Jaakkola
Streaming Min-max Hypergraph Partitioning
Dan Alistarh, Jennifer Iglesias, Milan Vojnovic
Learning structured densities via infinite dimensional exponential families
Siqi Sun, Mladen Kolar, Jinbo Xu
Exploring Models and Data for Image Question Answering
Mengye Ren, Ryan Kiros, Richard Zemel
Reflection, Refraction, and Hamiltonian Monte Carlo
Hadi Mohasel Afshar, Justin Domke
Regularization Path of Cross-Validation Error Lower Bounds
Atsushi Shibagaki, Yoshiki Suzuki, Masayuki Karasuyama et al.
Mind the Gap: A Generative Approach to Interpretable Feature Selection and Extraction
Been Kim, Julie A Shah, Finale Doshi-Velez
Sample Efficient Path Integral Control under Uncertainty
Yunpeng Pan, Evangelos Theodorou, Michail Kontitsis
Sample Complexity of Learning Mahalanobis Distance Metrics
Nakul Verma, Kristin Branson
Probabilistic Line Searches for Stochastic Optimization
Maren Mahsereci, Philipp Hennig
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings
Piyush Rai, Changwei Hu, Ricardo Henao et al.
Communication Complexity of Distributed Convex Learning and Optimization
Yossi Arjevani, Ohad Shamir
Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo et al.
A Gaussian Process Model of Quasar Spectral Energy Distributions
Andrew Miller, Albert Wu, Jeff Regier et al.
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier
Online Rank Elicitation for Plackett-Luce: A Dueling Bandits Approach
Balázs Szörényi, Róbert Busa-Fekete, Adil Paul et al.
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path
Daniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvari