Papers
4,025 papers found
On Estimation and Selection for Topic Models
Matt Taddy
Online Clustering of Processes
Azadeh Khaleghi, Daniil Ryabko, Jeremie Mary et al.
Online Clustering with Experts
Anna Choromanska, Claire Monteleoni
Online Incremental Feature Learning with Denoising Autoencoders
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits
Yasin Abbasi-Yadkori, David Pal, Csaba Szepesvari
On Nonparametric Guidance for Learning Autoencoder Representations
Jasper Snoek, Ryan Adams, Hugo Larochelle
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models
David Buchman, Mark Schmidt, Shakir Mohamed et al.
Optimistic planning for Markov decision processes
Lucian Busoniu, Remi Munos
Part & Clamp: Efficient Structured Output Learning
Patrick Pletscher, Cheng Soon Ong
Perturbation based Large Margin Approach for Ranking
Eunho Yang, Ambuj Tewari, Pradeep Ravikumar
Primal-Dual methods for sparse constrained matrix completion
Yu Xin, Tommi Jaakkola
Protocols for Learning Classifiers on Distributed Data
Hal Daume III, Jeff Phillips, Avishek Saha et al.
Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs
Hyokun Yun, S V N Vishwanathan
Random Feature Maps for Dot Product Kernels
Purushottam Kar, Harish Karnick
Randomized Optimum Models for Structured Prediction
Daniel Tarlow, Ryan Adams, Richard Zemel
Regression for sets of polynomial equations
Franz Kiraly, Paul Von Buenau, Jan Muller et al.
Regularization Paths with Guarantees for Convex Semidefinite Optimization
Joachim Giesen, Martin Jaggi, Soeren Laue
Robust Multi-task Regression with Grossly Corrupted Observations
Huan Xu, Chenlei Leng
Sample Complexity of Composite Likelihood
Joseph Bradley, Carlos Guestrin
Scalable Inference on Kingman’s Coalescent using Pair Similarity
Dilan Gorur, Levi Boyles, Max Welling
Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach
Kai Zhang, Liang Lan, Zhuang Wang et al.
Sparse Additive Machine
Tuo Zhao, Han Liu