Abstract is missing.
- Online Bandit Learning against an Adaptive Adversary: from Regret to Policy RegretOfer Dekel, Ambuj Tewari, Raman Arora. [doi]
- Smoothness and Structure Learning by Proxy Benjamin Yackley, Terran Lane. [doi]
- Dirichlet Process with Mixed Random Measures: A Nonparametric Topic Model for Labeled DataDongwoo Kim, Suin Kim, Alice H. Oh. [doi]
- Batch Active Learning via Coordinated MatchingJavad Azimi, Alan Fern, Xiaoli Zhang Fern, Glencora Borradaile, Brent Heeringa. [doi]
- Approximate Dynamic Programming By Minimizing Distributionally Robust BoundsMarek Petrik. [doi]
- Optimizing F-measure: A Tale of Two ApproachesYe Nan, Kian Ming Adam Chai, Wee Sun Lee, Hai Leong Chieu. [doi]
- Fast Training of Nonlinear Embedding AlgorithmsMax Vladymyrov, Miguel Á. Carreira-Perpiñán. [doi]
- Flexible Modeling of Latent Task Structures in Multitask LearningAlexandre Passos, Piyush Rai, Jacques Wainer, Hal Daumé III. [doi]
- Two Manifold Problems with Applications to Nonlinear System IdentificationByron Boots, Geoffrey J. Gordon. [doi]
- Dimensionality Reduction by Local Discriminative GaussiansNathan Parrish, Maya R. Gupta. [doi]
- How To Grade a Test Without Knowing the Answers - A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude TestingYoram Bachrach, Thore Graepel, Tom Minka, John Guiver. [doi]
- A Hybrid Algorithm for Convex Semidefinite OptimizationSören Laue. [doi]
- Shortest path distance in random k-nearest neighbor graphsMorteza Alamgir, Ulrike von Luxburg. [doi]
- Residual Components AnalysisAlfredo A. Kalaitzis, Neil D. Lawrence. [doi]
- PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class ClassificationEmilie Morvant, Sokol Koço, Liva Ralaivola. [doi]
- Learning Object Arrangements in 3D Scenes using Human ContextYun Jiang, Marcus Lim, Ashutosh Saxena. [doi]
- Exponential Regret Bounds for Gaussian Process Bandits with Deterministic ObservationsNando de Freitas, Alex J. Smola, Masrour Zoghi. [doi]
- Compact Hyperplane Hashing with Bilinear FunctionsWei Liu, Jun Wang 0006, Yadong Mu, Sanjiv Kumar, Shih-Fu Chang. [doi]
- Infinite Tucker Decomposition: Nonparametric Bayesian Models for Multiway Data AnalysisZenglin Xu, Feng Yan, Alan Qi. [doi]
- LPQP for MAP: Putting LP Solvers to Better UsePatrick Pletscher, Sharon Wulff. [doi]
- Copula-based Kernel Dependency MeasuresBarnabás Póczos, Zoubin Ghahramani, Jeff G. Schneider. [doi]
- Hierarchical Exploration for Accelerating Contextual BanditsYisong Yue, Sue Ann Hong, Carlos Guestrin. [doi]
- Is margin preserved after random projection?Qinfeng Shi, Chunhua Shen, Rhys Hill, Anton van den Hengel. [doi]
- Robust Classification with Adiabatic Quantum OptimizationVasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven. [doi]
- Near-Optimal BRL using Optimistic Local TransitionsMauricio Araya-López, Olivier Buffet, Vincent Thomas. [doi]
- State-Space Inference for Non-Linear Latent Force Models with Application to Satellite Orbit PredictionJouni Hartikainen, Mari Seppänen, Simo Särkkä. [doi]
- The Big Data BootstrapAriel Kleiner, Ameet Talwalkar, Purnamrita Sarkar, Michael I. Jordan. [doi]
- Conditional Sparse Coding and Grouped Multivariate RegressionMin Xu, John D. Lafferty. [doi]
- Consistent Covariance Selection From Data With Missing ValuesMladen Kolar, Eric P. Xing. [doi]
- Manifold Relevance DeterminationAndreas C. Damianou, Carl Henrik Ek, Michalis K. Titsias, Neil D. Lawrence. [doi]
- Cross Language Text Classification via Subspace Co-regularized Multi-view Learning Yuhong Guo, Min Xiao. [doi]
- Fast approximation of matrix coherence and statistical leverageMichael W. Mahoney, Petros Drineas, Malik Magdon-Ismail, David P. Woodruff. [doi]
- Learning the Experts for Online Sequence PredictionElad Eban, Aharon Birnbaum, Shai Shalev-Shwartz, Amir Globerson. [doi]
- 1 Regularization ProblemsChad Scherrer, Mahantesh Halappanavar, Ambuj Tewari, David Haglin. [doi]
- Monte Carlo Bayesian Reinforcement LearningYi Wang 0006, Kok Sung Won, David Hsu, Wee Sun Lee. [doi]
- Latent Multi-group Membership Graph ModelMyunghwan Kim 0002, Jure Leskovec. [doi]
- Unachievable Region in Precision-Recall Space and Its Effect on Empirical EvaluationKendrick Boyd, Jesse Davis, David Page, Vítor Santos Costa. [doi]
- Learning Invariant Representations with Local TransformationsKihyuk Sohn, Honglak Lee. [doi]
- Distributed Parameter Estimation via Pseudo-likelihood Qiang Liu, Alexander T. Ihler. [doi]
- Isoelastic Agents and Wealth Updates in Machine Learning MarketsAmos J. Storkey, Jono Millin, Krzysztof Geras. [doi]
- Nonparametric variational inferenceSamuel Gershman, Matthew D. Hoffman, David M. Blei. [doi]
- Structured Learning from Partial AnnotationsXinghua Lou, Fred A. Hamprecht. [doi]
- AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class ProblemPeng Sun, Mark D. Reid, Jie Zhou. [doi]
- Information-theoretic Semi-supervised Metric Learning via Entropy RegularizationGang Niu, Bo Dai, Makoto Yamada, Masashi Sugiyama. [doi]
- Safe Exploration in Markov Decision Processes Teodor Mihai Moldovan, Pieter Abbeel. [doi]
- High Dimensional Semiparametric Gaussian Copula Graphical ModelsHan Liu, Fang Han, Ming Yuan, John D. Lafferty, Larry A. Wasserman. [doi]
- Poisoning Attacks against Support Vector MachinesBattista Biggio, Blaine Nelson, Pavel Laskov. [doi]
- Collaborative Topic Regression with Social Matrix Factorization for Recommendation SystemsSanjay Purushotham, Yan Liu. [doi]
- Variational Inference in Non-negative Factorial Hidden Markov Models for Efficient Audio Source SeparationGautham J. Mysore, Maneesh Sahani. [doi]
- Canonical Trends: Detecting Trend Setters in Web DataFelix Bießmann, Jens-Michalis Papaioannou, Mikio Braun, Andreas Harth. [doi]
- Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex RelaxationsJames Neufeld, Yaoliang Yu, Xinhua Zhang, Ryan Kiros, Dale Schuurmans. [doi]
- Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie ModelingYan Liu 0002, Mohammad Taha Bahadori, Hongfei Li. [doi]
- Learning to Label Aerial Images from Noisy DataVolodymyr Mnih, Geoffrey E. Hinton. [doi]
- Stochastic Smoothing for Nonsmooth Minimizations: Accelerating SGD by Exploiting StructureHua Ouyang, Alexander G. Gray. [doi]
- A Proximal-Gradient Homotopy Method for the L1-Regularized Least-Squares ProblemLin Xiao, Tong Zhang 0001. [doi]
- Multiple Kernel Learning from Noisy Labels by Stochastic ProgrammingTianbao Yang, Mehrdad Mahdavi, Rong Jin, Lijun Zhang, Yang Zhou. [doi]
- Bayesian Watermark AttacksIvo Shterev, David B. Dunson. [doi]
- Bayesian Conditional CointegrationChris Bracegirdle, David Barber. [doi]
- On the Equivalence between Herding and Conditional Gradient AlgorithmsFrancis Bach, Simon Lacoste-Julien, Guillaume Obozinski. [doi]
- Variational Bayesian Inference with Stochastic SearchJohn William Paisley, David M. Blei, Michael I. Jordan. [doi]
- A Joint Model of Language and Perception for Grounded Attribute LearningCynthia Matuszek, Nicholas FitzGerald, Luke S. Zettlemoyer, Liefeng Bo, Dieter Fox. [doi]
- Capturing topical content with frequency and exclusivityJonathan Bischof, Edoardo Airoldi. [doi]
- Similarity Learning for Provably Accurate Sparse Linear ClassificationAurélien Bellet, Amaury Habrard, Marc Sebban. [doi]
- On causal and anticausal learningBernhard Schölkopf, Dominik Janzing, Jonas Peters, Eleni Sgouritsa, Kun Zhang, Joris M. Mooij. [doi]
- Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution MatchingMarthinus Christoffel du Plessis, Masashi Sugiyama. [doi]
- Efficient Euclidean Projections onto the Intersection of Norm BallsAdams Wei Yu, Hao Su, Fei-Fei Li. [doi]
- Bayesian Posterior Sampling via Stochastic Gradient Fisher ScoringSungjin Ahn, Anoop Korattikara Balan, Max Welling. [doi]
- Learning Parameterized SkillsBruno C. da Silva, George Konidaris, Andrew G. Barto. [doi]
- Robust PCA in High-dimension: A Deterministic ApproachJiashi Feng, Huan Xu, Shuicheng Yan. [doi]
- Building high-level features using large scale unsupervised learningQuoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng. [doi]
- Utilizing Static Analysis and Code Generation to Accelerate Neural NetworksLawrence C. McAfee, Kunle Olukotun. [doi]
- Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal CoversClément Farabet, Camille Couprie, Laurent Najman, Yann LeCun. [doi]
- Using CCA to improve CCA: A new spectral method for estimating vector models of wordsParamveer S. Dhillon, Jordan Rodu, Dean P. Foster, Lyle H. Ungar. [doi]
- Quasi-Newton Methods: A New DirectionPhilipp Hennig, Martin Kiefel. [doi]
- Deep Mixtures of Factor AnalysersYichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton. [doi]
- Copula Mixture Model for Dependency-seeking ClusteringMélanie Rey, Volker Roth. [doi]
- Robust Multiple Manifold Structure LearningDian Gong, Xuemei Zhao, Gérard G. Medioni. [doi]
- Predicting accurate probabilities with a ranking lossAditya Krishna Menon, Xiaoqian Jiang, Shankar Vembu, Charles Elkan, Lucila Ohno-Machado. [doi]
- Bounded Planning in Passive POMDPsRoy Fox, Naftali Tishby. [doi]
- Clustering to Maximize the Ratio of Split to DiameterJiabing Wang, Jiaye Chen. [doi]
- Lightning Does Not Strike Twice: Robust MDPs with Coupled UncertaintyShie Mannor, Ofir Mebel, Huan Xu. [doi]
- Discovering Support and Affiliated Features from Very High DimensionsYiteng Zhai, Mingkui Tan, Ivor W. Tsang, Yew-Soon Ong. [doi]
- Gaussian Process Regression NetworksAndrew Gordon Wilson, David A. Knowles, Zoubin Ghahramani. [doi]
- Discriminative Probabilistic Prototype LearningEdwin V. Bonilla, Antonio Robles-Kelly. [doi]
- Linear Regression with Limited ObservationElad Hazan, Tomer Koren. [doi]
- Fast Computation of Subpath Kernel for TreesDaisuke Kimura, Hisashi Kashima. [doi]
- Factorized Asymptotic Bayesian Hidden Markov ModelsRyohei Fujimaki, Kohei Hayashi. [doi]
- Improved Information Gain Estimates for Decision Tree InductionSebastian Nowozin. [doi]
- Minimizing The Misclassification Error Rate Using a Surrogate Convex LossShai Ben-David, David Loker, Nathan Srebro, Karthik Sridharan. [doi]
- Feature Selection via Probabilistic OutputsAndrea Pohoreckyj Danyluk, Nicholas Arnosti. [doi]
- On the Sample Complexity of Reinforcement Learning with a Generative Model Mohammad Gheshlaghi Azar, Rémi Munos, Bert Kappen. [doi]
- A Unified Robust Classification ModelAkiko Takeda, Hiroyuki Mitsugi, Takafumi Kanamori. [doi]
- Policy Gradients with Variance Related Risk CriteriaDotan Di Castro, Aviv Tamar, Shie Mannor. [doi]
- Conditional mean embeddings as regressorsSteffen Grünewälder, Guy Lever, Arthur Gretton, Luca Baldassarre, Sam Patterson, Massimiliano Pontil. [doi]
- Nonparametric Link Prediction in Dynamic NetworksPurnamrita Sarkar, Deepayan Chakrabarti, Michael I. Jordan. [doi]
- Local Loss Optimization in Operator Models: A New Insight into Spectral LearningBorja Balle, Ariadna Quattoni, Xavier Carreras. [doi]
- Revisiting k-means: New Algorithms via Bayesian NonparametricsBrian Kulis, Michael I. Jordan. [doi]
- Levy Measure Decompositions for the Beta and Gamma ProcessesYingjian Wang, Lawrence Carin. [doi]
- Convex Multitask Learning with Flexible Task ClustersWenliang Zhong, James Tin-Yau Kwok. [doi]
- Small-sample brain mapping: sparse recovery on spatially correlated designs with randomization and clusteringGaël Varoquaux, Alexandre Gramfort, Bertrand Thirion. [doi]
- A convex relaxation for weakly supervised classifiersArmand Joulin, Francis Bach. [doi]
- Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink PaintingNing Xie, Hirotaka Hachiya, Masashi Sugiyama. [doi]
- Sparse stochastic inference for latent Dirichlet allocationDavid M. Mimno, Matthew D. Hoffman, David M. Blei. [doi]
- Adaptive Canonical Correlation Analysis Based On Matrix ManifoldsFlorian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy. [doi]
- An Efficient Approach to Sparse Linear Discriminant AnalysisLuis Francisco Sánchez Merchante, Yves Grandvalet, Gérard Govaert. [doi]
- Inferring Latent Structure From Mixed Real and Categorical Relational DataEsther Salazar, Lawrence Carin. [doi]
- Learning the Dependence Graph of Time Series with Latent FactorsAli Jalali, Sujay Sanghavi. [doi]
- Linear Off-Policy Actor-CriticThomas Degris, Martha White, Richard S. Sutton. [doi]
- Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit DesignLauren Hannah, David B. Dunson. [doi]
- Rethinking Collapsed Variational Bayes Inference for LDAIssei Sato, Hiroshi Nakagawa. [doi]
- Improved Nystrom Low-rank Decomposition with PriorsKai Zhang, Liang Lan, Jun Liu, Andreas Rauber. [doi]
- Subgraph Matching Kernels for Attributed GraphsNils Kriege, Petra Mutzel. [doi]
- Latent Collaborative RetrievalJason Weston, Chong Wang, Ron J. Weiss, Adam Berenzweig. [doi]
- Training Restricted Boltzmann Machines on Word ObservationsGeorge E. Dahl, Ryan Prescott Adams, Hugo Larochelle. [doi]
- Comparison-Based Learning with Rank NetsAmin Karbasi, Stratis Ioannidis, Laurent Massoulié. [doi]
- Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning Shakir Mohamed, Katherine A. Heller, Zoubin Ghahramani. [doi]
- Online Alternating Direction MethodHuahua Wang, Arindam Banerjee. [doi]
- Hypothesis testing using pairwise distances and associated kernelsDino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu. [doi]
- Clustering using Max-norm Constrained OptimizationAli Jalali, Nathan Srebro. [doi]
- Modeling Images using Transformed Indian Buffet ProcessesKe Zhai, Yuening Hu, Jordan L. Boyd-Graber, Sinead Williamson. [doi]
- Machine Learning that MattersKiri Wagstaff. [doi]
- A Simple Algorithm for Semi-supervised Learning with Improved Generalization Error BoundMing Ji, Tianbao Yang, Binbin Lin, Rong Jin, Jiawei Han. [doi]
- Making Gradient Descent Optimal for Strongly Convex Stochastic OptimizationAlexander Rakhlin, Ohad Shamir, Karthik Sridharan. [doi]
- An adaptive algorithm for finite stochastic partial monitoringGábor Bartók, Navid Zolghadr, Csaba Szepesvári. [doi]
- Marginalized Denoising Autoencoders for Domain AdaptationMinmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha. [doi]
- Estimating the Hessian by Back-propagating CurvatureJames Martens, Ilya Sutskever, Kevin Swersky. [doi]
- A fast and simple algorithm for training neural probabilistic language modelsAndriy Mnih, Yee Whye Teh. [doi]
- Total Variation and Euler's Elastica for Supervised LearningTong Lin, Hanlin Xue, Ling Wang, Hongbin Zha. [doi]
- Consistent Multilabel Ranking through Univariate LossesKrzysztof Dembczynski, Wojciech Kotlowski, Eyke Hüllermeier. [doi]
- Multi-level Lasso for Sparse Multi-task RegressionAurelie C. Lozano, Grzegorz Swirszcz. [doi]
- Efficient Structured Prediction with Latent Variables for General Graphical ModelsAlexander G. Schwing, Tamir Hazan, Marc Pollefeys, Raquel Urtasun. [doi]
- Deep Lambertian NetworksYichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hinton. [doi]
- Fast Prediction of New Feature UtilityHoyt A. Koepke, Mikhail Bilenko. [doi]
- Influence Maximization in Continuous Time Diffusion NetworksManuel Gomez-Rodriguez, Bernhard Schölkopf. [doi]
- Learning Force Control Policies for Compliant Robotic ManipulationMrinal Kalakrishnan, Ludovic Righetti, Peter Pastor, Stefan Schaal. [doi]
- Convergence of the EM Algorithm for Gaussian Mixtures with Unbalanced Mixing CoefficientsIftekhar Naim, Daniel Gildea. [doi]
- Output Space Search for Structured PredictionJanardhan Rao Doppa, Alan Fern, Prasad Tadepalli. [doi]
- Gap Filling in the Plant Kingdom - Trait Prediction Using Hierarchical Probabilistic Matrix FactorizationHanhuai Shan, Jens Kattge, Peter Reich, Arindam Banerjee, Franziska Schrodt, Markus Reichstein. [doi]
- Greedy Algorithms for Sparse Reinforcement LearningChristopher Painter-Wakefield, Ronald Parr. [doi]
- A Topic Model for Melodic SequencesAthina Spiliopoulou, Amos J. Storkey. [doi]
- Incorporating Domain Knowledge in Matching Problems via Harmonic AnalysisDeepti Pachauri, Maxwell D. Collins, Vikas Singh. [doi]
- Exact Soft Confidence-Weighted LearningSteven C. H. Hoi, Jialei Wang, Peilin Zhao. [doi]
- Efficient and Practical Stochastic Subgradient Descent for Nuclear Norm RegularizationHaim Avron, Satyen Kale, Shiva Prasad Kasiviswanathan, Vikas Sindhwani. [doi]
- Submodular Inference of Diffusion Networks from Multiple TreesManuel Gomez-Rodriguez, Bernhard Schölkopf. [doi]
- Sequential Nonparametric RegressionHaijie Gu, John D. Lafferty. [doi]
- Modelling transition dynamics in MDPs with RKHS embeddingsSteffen Grünewälder, Guy Lever, Luca Baldassarre, Massimiliano Pontil, Arthur Gretton. [doi]
- Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising ModelsJean Honorio. [doi]
- Improved Estimation in Time Varying ModelsDoina Precup, Philip Bachman. [doi]
- Approximate Principal Direction TreesMark McCartin-Lim, Andrew McGregor, Rui Wang. [doi]
- Learning Efficient Structured Sparse ModelsAlexander M. Bronstein, Pablo Sprechmann, Guillermo Sapiro. [doi]
- Analysis of Kernel Mean Matching under Covariate ShiftYaoliang Yu, Csaba Szepesvári. [doi]
- Convergence Rates for Differentially Private Statistical EstimationKamalika Chaudhuri, Daniel Hsu. [doi]
- Variance Function Estimation in High-dimensionsMladen Kolar, James Sharpnack. [doi]
- Compositional Planning Using Optimal Option ModelsDavid Silver, Kamil Ciosek. [doi]
- A Hierarchical Dirichlet Process Model with Multiple Levels of Clustering for Human EEG Seizure ModelingDrausin Wulsin, Shane Jensen, Brian Litt. [doi]
- TrueLabel + Confusions: A Spectrum of Probabilistic Models in Analyzing Multiple RatingsChao Liu, Yi-Min Wang. [doi]
- Data-driven Web DesignRanjitha Kumar, Jerry O. Talton, Salman Ahmad, Scott R. Klemmer. [doi]
- PAC Subset Selection in Stochastic Multi-armed BanditsShivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, Peter Stone. [doi]
- A Split-Merge Framework for Comparing ClusteringsQiaoliang Xiang, Qi Mao, Kian Ming Adam Chai, Hai Leong Chieu, Ivor W. Tsang, Zhendong Zhao. [doi]
- A Bayesian Approach to Approximate Joint Diagonalization of Square MatricesMingjun Zhong, Mark A. Girolami. [doi]
- Complexity Analysis of the Lasso Regularization PathJulien Mairal, Bin Yu. [doi]
- A Dantzig Selector Approach to Temporal Difference LearningMatthieu Geist, Bruno Scherrer, Alessandro Lazaric, Mohammad Ghavamzadeh. [doi]
- An Infinite Latent Attribute Model for Network DataKonstantina Palla, David A. Knowles, Zoubin Ghahramani. [doi]
- A Generative Process for Contractive Auto-EncodersSalah Rifai, Yann Dauphin, Pascal Vincent, Yoshua Bengio. [doi]
- Predicting Consumer Behavior in Commerce SearchOr Sheffet, Nina Mishra, Samuel Ieong. [doi]
- On-Line Portfolio Selection with Moving Average ReversionBin Li, Steven C. H. Hoi. [doi]
- Incorporating Causal Prior Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral GraphsGiorgos Borboudakis, Ioannis Tsamardinos. [doi]
- Bayesian Nonexhaustive Learning for Online Discovery and Modeling of Emerging ClassesMurat Dundar, Ferit Akova, Alan Qi, Bartek Rajwa. [doi]
- Tighter Variational Representations of f-Divergences via Restriction to Probability MeasuresAvraham Ruderman, Mark D. Reid, Dario García-García, James Petterson. [doi]
- The Convexity and Design of Composite Multiclass LossesMark D. Reid, Robert C. Williamson, Peng Sun. [doi]
- Continuous Inverse Optimal Control with Locally Optimal ExamplesSergey Levine, Vladlen Koltun. [doi]
- The Kernelized Stochastic Batch PerceptronAndrew Cotter, Shai Shalev-Shwartz, Nathan Srebro. [doi]
- Path Integral Policy Improvement with Covariance Matrix AdaptationFreek Stulp, Olivier Sigaud. [doi]
- A Combinatorial Algebraic Approach for the Identifiability of Low-Rank Matrix CompletionFranz J. Király, Ryota Tomioka. [doi]
- Efficient Active Algorithms for Hierarchical ClusteringAkshay Krishnamurthy, Sivaraman Balakrishnan, Min Xu, Aarti Singh. [doi]
- The Greedy Miser: Learning under Test-time BudgetsZhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle. [doi]
- Stability of matrix factorization for collaborative filteringYu-Xiang Wang, Huan Xu. [doi]
- The Landmark Selection Method for Multiple Output PredictionKrishnakumar Balasubramanian, Guy Lebanon. [doi]
- Distributed Tree KernelsFabio Massimo Zanzotto, Lorenzo Dell'Arciprete. [doi]
- Gaussian Process Quantile Regression using Expectation PropagationAlexis Boukouvalas, Remi Barillec, Dan Cornford. [doi]
- Dependent Hierarchical Normalized Random Measures for Dynamic Topic ModelingChangyou Chen, Nan Ding, Wray L. Buntine. [doi]
- Bayesian Efficient Multiple Kernel LearningMehmet Gönen. [doi]
- Hybrid Batch Bayesian OptimizationJavad Azimi, Ali Jalali, Xiaoli Zhang Fern. [doi]
- Learning to Identify Regular Expressions that Describe Email CampaignsPaul Prasse, Christoph Sawade, Niels Landwehr, Tobias Scheffer. [doi]
- Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and TranscriptionNicolas Boulanger-Lewandowski, Yoshua Bengio, Pascal Vincent. [doi]
- Apprenticeship Learning for Model Parameters of Partially Observable EnvironmentsTakaki Makino, Johane Takeuchi. [doi]
- A Complete Analysis of the l_1, p Group-LassoJulia E. Vogt, Volker Roth. [doi]
- Decoupling Exploration and Exploitation in Multi-Armed BanditsOrly Avner, Shie Mannor, Ohad Shamir. [doi]
- Clustering by Low-Rank Doubly Stochastic Matrix DecompositionZhirong Yang, Erkki Oja. [doi]
- Exact Maximum Margin Structure Learning of Bayesian NetworksRobert Peharz, Franz Pernkopf. [doi]
- Estimation of Simultaneously Sparse and Low Rank MatricesPierre-André Savalle, Emile Richard, Nicolas Vayatis. [doi]
- Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain AdaptationYuan Shi, Fei Sha. [doi]
- Online Structured Prediction via Coactive LearningPannaga Shivaswamy, Thorsten Joachims. [doi]
- Projection-free Online LearningElad Hazan, Satyen Kale. [doi]
- Adaptive Regularization for Similarity MeasuresKoby Crammer, Gal Chechik. [doi]
- Approximate Modified Policy IterationBruno Scherrer, Victor Gabillon, Mohammad Ghavamzadeh, Matthieu Geist. [doi]
- Groupwise Constrained Reconstruction for Subspace ClusteringRuijiang Li, Bin Li, Cheng Jin, Xiangyang Xue. [doi]
- Finding Botnets Using Minimal Graph ClusteringsPeter Haider, Tobias Scheffer. [doi]
- Cross-Domain Multitask Learning with Latent Probit ModelsShaobo Han, Xuejun Liao, Lawrence Carin. [doi]
- Large Scale Variational Bayesian Inference for Structured Scale Mixture ModelsYoung Jun Ko, Matthias Seeger. [doi]
- Learning the Central Events and Participants in Unlabeled TextNathanael Chambers, Dan Jurafsky. [doi]
- On multi-view feature learningRoland Memisevic. [doi]
- Sparse Support Vector Infinite PushAlain Rakotomamonjy. [doi]
- Fast classification using sparse decision DAGsRóbert Busa-Fekete, Djalel Benbouzid, Balázs Kégl. [doi]
- Statistical linear estimation with penalized estimators: an application to reinforcement learningBernardo Avila Pires, Csaba Szepesvári. [doi]
- Learning Task Grouping and Overlap in Multi-task LearningAbhishek Kumar, Hal Daumé III. [doi]
- Max-Margin Nonparametric Latent Feature Models for Link PredictionJun Zhu. [doi]
- Large-Scale Feature Learning With Spike-and-Slab Sparse CodingIan J. Goodfellow, Aaron C. Courville, Yoshua Bengio. [doi]
- No-Regret Learning in Extensive-Form Games with Imperfect RecallMarc Lanctot, Richard G. Gibson, Neil Burch, Michael Bowling. [doi]
- Exemplar-SVMs for Visual Ob ject Detection, Label Transfer and Image RetrievalTomasz Malisiewicz, Abhinav Shrivastava, Abhinav Gupta, Alexei A. Efros. [doi]
- Group Sparse Additive ModelsJunming Yin, Xi Chen, Eric P. Xing. [doi]
- Agglomerative Bregman ClusteringMatus Telgarsky, Sanjoy Dasgupta. [doi]
- Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online LearningSteven C. H. Hoi, Jialei Wang, Peilin Zhao, Rong Jin, Pengcheng Wu. [doi]
- On the Size of the Online Kernel Sparsification DictionaryYi Sun, Faustino J. Gomez, Jürgen Schmidhuber. [doi]
- Joint Optimization and Variable Selection of High-dimensional Gaussian ProcessesBo Chen, Rui Castro, Andreas Krause. [doi]
- Plug-in martingales for testing exchangeability on-lineValentina Fedorova, Alex J. Gammerman, Ilia Nouretdinov, Volodya Vovk. [doi]
- An Iterative Locally Linear Embedding AlgorithmDeguang Kong, Chris H. Q. Ding. [doi]
- Maximum Margin Output CodingYi Zhang, Jeff Schneider. [doi]
- The Nonparametric Metadata Dependent Relational ModelDae-Il Kim, Michael C. Hughes, Erik B. Sudderth. [doi]
- Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug EventsJesse Davis, Vítor Santos Costa, Elizabeth Berg, David Page, Peggy L. Peissig, Michael Caldwell. [doi]
- Bayesian Optimal Active Search and SurveyingRoman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff Schneider, Richard Mann. [doi]
- Modeling Latent Variable Uncertainty for Loss-based LearningM. Pawan Kumar, Benjamin Packer, Daphne Koller. [doi]
- Efficient Decomposed Learning for Structured PredictionRajhans Samdani, Dan Roth. [doi]
- Communications Inspired Linear Discriminant AnalysisMinhua Chen, William R. Carson, Miguel R. D. Rodrigues, Lawrence Carin, A. Robert Calderbank. [doi]
- The Most Persistent Soft-Clique in a Set of Sampled GraphsNovi Quadrianto, Chao Chen, Christoph H. Lampert. [doi]
- Anytime Marginal MAP InferenceDenis Deratani Mauá, Cassio Polpo de Campos. [doi]
- Learning with Augmented Features for Heterogeneous Domain AdaptationLixin Duan, Dong Xu, Ivor W. Tsang. [doi]
- High-Dimensional Covariance Decomposition into Sparse Markov and Independence DomainsMajid Janzamin, Animashree Anandkumar. [doi]
- A Graphical Model Formulation of Collaborative Filtering Neighbourhood Methods with Fast Maximum Entropy TrainingAaron Defazio, Tibério S. Caetano. [doi]
- An Online Boosting Algorithm with Theoretical JustificationsShang-Tse Chen, Hsuan-Tien Lin, Chi-Jen Lu. [doi]
- A Generalized Loop Correction Method for Approximate Inference in Graphical ModelsSiamak (Moshen) Ravanbakhsh, Chun-Nam Yu, Russell Greiner. [doi]
- A Binary Classification Framework for Two-Stage Multiple Kernel LearningAbhishek Kumar, Alexandru Niculescu-Mizil, Koray Kavukcuoglu, Hal Daumé III. [doi]
- On Local RegretMichael Bowling, Martin Zinkevich. [doi]
- Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit OptimizationThomas Desautels, Andreas Krause, Joel W. Burdick. [doi]
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