Papers
Minimizing Uncertainty in Pipelines
Nilesh Dalvi, Aditya Parameswaran, Vibhor Rastogi
Mirror Descent Meets Fixed Share (and feels no regret)
Nicolò Cesa-bianchi, Pierre Gaillard, Gabor Lugosi et al.
Mixability in Statistical Learning
Tim V. Erven, Peter Grünwald, Mark D. Reid et al.
Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions
Mathieu Sinn, Bei Chen
Modelling Reciprocating Relationships with Hawkes Processes
Charles Blundell, Jeff Beck, Katherine A. Heller
Monte Carlo Methods for Maximum Margin Supervised Topic Models
Qixia Jiang, Jun Zhu, Maosong Sun et al.
Multiclass Learning Approaches: A Theoretical Comparison with Implications
Amit Daniely, Sivan Sabato, Shai S. Shwartz
Multiclass Learning with Simplex Coding
Youssef Mroueh, Tomaso Poggio, Lorenzo Rosasco et al.
Multi-criteria Anomaly Detection using Pareto Depth Analysis
Ko-jen Hsiao, Kevin Xu, Jeff Calder et al.
Multilabel Classification using Bayesian Compressed Sensing
Ashish Kapoor, Raajay Viswanathan, Prateek Jain
Multimodal Learning with Deep Boltzmann Machines
Nitish Srivastava, Ruslan Salakhutdinov
Multiple Choice Learning: Learning to Produce Multiple Structured Outputs
Abner Guzmán-rivera, Dhruv Batra, Pushmeet Kohli
Multiple Operator-valued Kernel Learning
Hachem Kadri, Alain Rakotomamonjy, Philippe Preux et al.
Multiplicative Forests for Continuous-Time Processes
Jeremy Weiss, Sriraam Natarajan, David Page
Multiresolution analysis on the symmetric group
Risi Kondor, Walter Dempsey
Multiresolution Gaussian Processes
Emily B. Fox, David B. Dunson
Multi-scale Hyper-time Hardware Emulation of Human Motor Nervous System Based on Spiking Neurons using FPGA
C. M. Niu, Sirish Nandyala, Won J. Sohn et al.
Multi-Stage Multi-Task Feature Learning
Pinghua Gong, Jieping Ye, Chang-shui Zhang
Multi-Task Averaging
Sergey Feldman, Maya Gupta, Bela Frigyik
Multi-task Vector Field Learning
Binbin Lin, Sen Yang, Chiyuan Zhang et al.
Natural Images, Gaussian Mixtures and Dead Leaves
Daniel Zoran, Yair Weiss
Near-optimal Differentially Private Principal Components
Kamalika Chaudhuri, Anand Sarwate, Kaushik Sinha
Near-Optimal MAP Inference for Determinantal Point Processes
Jennifer Gillenwater, Alex Kulesza, Ben Taskar
Neurally Plausible Reinforcement Learning of Working Memory Tasks
Jaldert Rombouts, Pieter Roelfsema, Sander M. Bohte
Neuronal Spike Generation Mechanism as an Oversampling, Noise-shaping A-to-D converter
Dmitri B. Chklovskii, Daniel Soudry