Papers
176,624 papers found
Improving QA Accuracy by Question Inversion
John Prager, Pablo Duboue, Jennifer Chu-Carroll
Improving Robot Navigation Through Self-Supervised Online Learning
B. Sofman, E. Lin, J. Bagnell et al.
Incremental Algorithms for Hierarchical Classification
Nicoló Cesa-Bianchi, Claudio Gentile, Luca Zaniboni
Incremental Support Vector Learning: Analysis, Implementation and Applications
Pavel Laskov, Christian Gehl, Stefan Krüger et al.
Inducing Metric Violations in Human Similarity Judgements
Julian Laub, Klaus-Robert Müller, Felix A. Wichmann et al.
Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach
Emanuel Kitzelmann, Ute Schmid
Inferring Network Structure from Co-Occurrences
Michael G. Rabbat, Mário Figueiredo, Robert Nowak
Infinite-Ï Limits For Tikhonov Regularization
Ross A. Lippert, Ryan M. Rifkin
Information Bottleneck for Non Co-Occurrence Data
Yevgeny Seldin, Noam Slonim, Naftali Tishby
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons
Stefan Klampfl, Wolfgang Maass, Robert A. Legenstein
In-Network PCA and Anomaly Detection
Ling Huang, Xuanlong Nguyen, Minos Garofalakis et al.
In Search of Non-Gaussian Components of a High-Dimensional Distribution
Gilles Blanchard, Motoaki Kawanabe, Masashi Sugiyama et al.
Integrated Planning and Control for Convex-bodied Nonholonomic systems using Local Feedback Control Policies
D. Conner, H. Choset, A. Rizzi
Inverse Kinematics for a Serial Chain with Joints Under Distance Constraints
L. Han, L. Rudolph
Isotonic Conditional Random Fields and Local Sentiment Flow
Yi Mao, Guy Lebanon
Kernel-Based Learning of Hierarchical Multilabel Classification Models
Juho Rousu, Craig Saunders, Sandor Szedmak et al.
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm
Robert Jenssen, Torbjørn Eltoft, Mark Girolami et al.
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
Andrea Passerini, Paolo Frasconi, Luc De Raedt
Kernels on Structured Objects Through Nested Histograms
Marco Cuturi, Kenji Fukumizu
Large Margin Component Analysis
Lorenzo Torresani, Kuang-chih Lee
Large Margin Hidden Markov Models for Automatic Speech Recognition
Fei Sha, Lawrence K. Saul
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural Prosthesis
Amit Gore, Shantanu Chakrabartty
Large Scale Hidden Semi-Markov SVMs
Gunnar Rätsch, Sören Sonnenburg
Large Scale Multiple Kernel Learning
Sören Sonnenburg, Gunnar Rätsch, Christin Schäfer et al.
Large-Scale Sparsified Manifold Regularization
Ivor W. Tsang, James T. Kwok