Papers
173,579 papers found
Multiple Operator-valued Kernel Learning
Hachem Kadri, Alain Rakotomamonjy, Philippe Preux et al.
Multiple Texture Boltzmann Machines
Jyri Kivinen, Christopher Williams
Multiplicative Forests for Continuous-Time Processes
Jeremy Weiss, Sriraam Natarajan, David Page
Multiresolution analysis on the symmetric group
Risi Kondor, Walter Dempsey
Multiresolution Deep Belief Networks
Yichuan Tang, Abdel-Rahman Mohamed
Multiresolution Gaussian Processes
Emily B. Fox, David B. Dunson
Multiresolution Mixture Modeling using Merging of Mixture Components
Prem Raj Adhikari, Jaakko Hollmén
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 Classifier Design
Kirill Trapeznikov, Venkatesh Saligrama, David Castañón
Multi-stage micro rockets for robotic insects
Mirko Kovac, Maria Bendana, Rohit Krishnan et al.
Multi-Stage Multi-Task Feature Learning
Pinghua Gong, Jieping Ye, Chang-shui Zhang
Multi-Target Regression with Rule Ensembles
Timo Aho, Bernard Ženko, Sašo Džeroski et al.
Multi-Task Averaging
Sergey Feldman, Maya Gupta, Bela Frigyik
Multi-task Regression using Minimal Penalties
Matthieu Solnon, Sylvain Arlot, Francis Bach
Multi-task Vector Field Learning
Binbin Lin, Sen Yang, Chiyuan Zhang et al.
Multi-view Positive and Unlabeled Learning
Joey Tianyi Zhou, Sinno Jialin Pan, Qi Mao et al.
M-Width: Stability and Accuracy of Haptic Rendering of Virtual Mass
Nick Colonnese, Allison Okamura
Natural Images, Gaussian Mixtures and Dead Leaves
Daniel Zoran, Yair Weiss
Near-Optimal Algorithms for Online Matrix Prediction
Elad Hazan, Satyen Kale, Shai Shalev-Shwartz
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
New Bounds for Learning Intervals with Implications for Semi-Supervised Learning
David P. Helmbold, Philip M. Long
Newton-Like Methods for Sparse Inverse Covariance Estimation
Figen Oztoprak, Jorge Nocedal, Steven Rennie et al.