Papers
Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models
Manfred Opper, Ulrich Paquet, Ole Winther
Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees
Nima Noorshams, Martin J. Wainwright
BudgetedSVM: A Toolbox for Scalable SVM Approximations
Nemanja Djuric, Liang Lan, Slobodan Vucetic et al.
Optimally Fuzzy Temporal Memory
Karthik H. Shankar, Marc W. Howard
Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory
Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto
Maximum Volume Clustering: A New Discriminative Clustering Approach
Gang Niu, Bo Dai, Lin Shang et al.
Keep It Simple And Sparse: Real-Time Action Recognition
Sean Ryan Fanello, Ilaria Gori, Giorgio Metta et al.
Efficient Active Learning of Halfspaces: An Aggressive Approach
Alon Gonen, Sivan Sabato, Shai Shalev-Shwartz
One-shot Learning Gesture Recognition from RGB-D Data Using Bag of Features
Jun Wan, Qiuqi Ruan, Wei Li et al.
Learning Bilinear Model for Matching Queries and Documents
Wei Wu, Zhengdong Lu, Hang Li
Greedy Feature Selection for Subspace Clustering
Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk
Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows
Julien Mairal, Bin Yu
On the Mutual Nearest Neighbors Estimate in Regression
Arnaud Guyader, Nick Hengartner
Tapkee: An Efficient Dimension Reduction Library
Sergey Lisitsyn, Christian Widmer, Fernando J. Iglesias Garcia
Orange: Data Mining Toolbox in Python
Janez Demšar, Tomaž Curk, Aleš Erjavec et al.
The Rate of Convergence of AdaBoost
Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
Message-Passing Algorithms for Quadratic Minimization
Nicholas Ruozzi, Sekhar Tatikonda
Gaussian Kullback-Leibler Approximate Inference
Edward Challis, David Barber
Segregating Event Streams and Noise with a Markov Renewal Process Model
Dan Stowell, Mark D. Plumbley
Language-Motivated Approaches to Action Recognition
Manavender R. Malgireddy, Ifeoma Nwogu, Venu Govindaraju
Convex and Scalable Weakly Labeled SVMs
Yu-Feng Li, Ivor W. Tsang, James T. Kwok et al.
Distribution-Dependent Sample Complexity of Large Margin Learning
Sivan Sabato, Nathan Srebro, Naftali Tishby
Construction of Approximation Spaces for Reinforcement Learning
Wendelin Böhmer, Steffen Grünewälder, Yun Shen et al.