Via Olivier Grisel's twitter feed, here are the second of the videos of the ICML2013 meeting hosted on the TechTalks.tv site: - Part 1 is here -

Track A: Nearest Neighbor and Metric Learning

- Entropic Affinities: Properties and Efficient Numerical ComputationAuthors: Max Vladymyrov; Miguel Carreira-Perpinan
- Learning Hash Functions Using Column GenerationAuthors: Xi Li; Guosheng Lin; Chunhua Shen; Anton van den Hengel; Anthony Dick
- Robust Structural Metric LearningAuthors: Daryl Lim; Gert Lanckriet; Brian McFee
- Revisiting the Nystrom method for improved large-scale machine learningAuthors: Alex Gittens; Michael Mahoney
- That was fast! Speeding up NN search of high dimensional distributionsAuthors: Emanuele Coviello; Adeel Mumtaz; Antoni Chan; Gert Lanckriet
- Stochastic k-Neighborhood Selection for Supervised and Unsupervised LearningAuthors: Daniel Tarlow; Kevin Swersky; Ilya Sutskever; Laurent Charlin; Rich Zemel
- Predictable Dual-View HashingAuthors: Mohammad Rastegari; Jonghyun Choi; Shobeir Fakhraei; Daume Hal; Larry Davis
- A unifying framework for vector-valued manifold regularization and multi-view learningAuthors: Minh Ha Quang; Loris Bazzani; Vittorio Murino

Compressed Sensing 2

- Learning Heteroscedastic Models by Convex Programming under Group SparsityAuthors: Arnak Dalalyan; Mohamed Hebiri; Katia Meziani; Joseph Salmon
- Noisy Sparse Subspace ClusteringAuthors: Yu-Xiang Wang; Huan Xu
- One-Bit Compressed Sensing: Provable Support and Vector RecoveryAuthors: Praneeth Netrapalli, Sivakant Gopi; Prateek Jain, Aditya Nori
- Smooth Sparse Coding via Marginal Regression for Learning Sparse RepresentationsAuthors: Krishnakumar Balasubramanian; Kai Yu; Guy Lebanon
- Sparse projections onto the simplexAuthors: Anastasios Kyrillidis; Stephen Becker; Volkan Cevher; Christoph Koch
- Intersecting singularities for multi-structured estimationAuthors: Emile Richard; Francis BACH; Jean-Philippe Vert
- Sparse Uncorrelated Linear Discriminant AnalysisAuthors: Xiaowei Zhang; Delin Chu
- Estimating Unknown Sparsity in Compressed SensingAuthors: Miles Lopes

Track B: General Methods

- Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation ModelAuthors: Min Xiao; Yuhong Guo
- Maximum Variance Correction with Application to A* SearchAuthors: Wenlin Chen; Kilian Weinberger; Yixin Chen
- Learning with Marginalized Corrupted FeaturesAuthors: Laurens van der Maaten; Minmin Chen; Stephen Tyree; Kilian Weinberger
- Scaling Multidimensional Gaussian Processes using Projected Additive ApproximationsAuthors: Elad Gilboa; Yunus Saatci; John Cunningham
- Nonparametric Mixture of Gaussian Processes with ConstraintsAuthors: James Ross; Jennifer Dy
- Fast Dual Variational Inference for Non-Conjugate Latent Gaussian ModelsAuthors: Mohammad Emtiyaz Khan; Aleksandr Aravkin; Michael Friedlander; Matthias Seeger
- Gaussian Process Vine Copulas for Multivariate DependenceAuthors: David Lopez-Paz; Jose Miguel Hernandez-Lobato; Ghahramani Zoubin
- Structure Discovery in Nonparametric Regression through Compositional Kernel SearchAuthors: David Duvenaud; James Lloyd; Roger Grosse; Joshua Tenenbaum; Ghahramani Zoubin
- Sequential Bayesian SearchAuthors: Zheng Wen; Branislav Kveton; Brian Eriksson; Sandilya Bhamidipati
- Kernelized Bayesian Matrix FactorizationAuthors: Mehmet G

Reinforcement learning 2

- Concurrent Reinforcement Learning from Customer Interaction SequencesAuthors: David Silver; Leonard Newnham; David Barker; Suzanne Weller; Jason McFall
- Modelling Sparse Dynamical Systems with Compressed Predictive State RepresentationsAuthors: William Hamilton; Mahdi Milani Fard,; Joelle Pineau
- Coco-Q: Learning in Stochastic Games with Side PaymentsAuthors: Elizabeth Hilliard; Eric Sodomka; Michael Littman; Amy Greenwald
- Guided Policy SearchAuthors: Sergey Levine; Vladlen Koltun
- The Cross-Entropy Method Optimizes for QuantilesAuthors: Sergiu Goschin; Ari Weinstein; Michael Littman

Track C: Transfer Learning

- Domain Generalization via Invariant Feature RepresentationAuthors: Krikamol Muandet; David Balduzzi, ; Bernhard Schoelkopf
- A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear ClassifiersAuthors: Pascal Germain; Amaury Habrard; Fran
- Sparse coding for multitask and transfer learningAuthors: Andreas Maurer; Massi Pontil; Bernardino Romera-Paredes
- Bayesian Games for Adversarial Regression ProblemsAuthors: Michael Gro
- Joint Transfer and Batch-mode Active LearningAuthors: Rita Chattopadhyay; Wei Fan; Ian Davidson; Sethuraman Panchanathan; Jieping Ye
- Multilinear Multitask LearningAuthors: Bernardino Romera-Paredes; Hane Aung; Nadia Bianchi-Berthouze; Massimiliano Pontil
- Stability and Hypothesis Transfer LearningAuthors: Ilja Kuzborskij; Francesco Orabona
- Multi-Task Learning with Gaussian Matrix Generalized Inverse Gaussian ModeAuthors: Ming Yang; Li Yingming; Zhang Zhongfei (Mark)

Topic Modeling 1

- A Practical Algorithm for Topic Modeling with Provable GuaranteesAuthors: Sanjeev Arora; Rong Ge; Yonatan Halpern; David Mimno; Ankur Moitra; David Sontag; Yichen Wu; Michael Zhu
- Online Latent Dirichlet Allocation with Infinite VocabularyAuthors: KE ZHAI; Jordan Boyd-Graber
- Gibbs Max-Margin Topic Models with Fast Sampling AlgorithmsAuthors: Jun Zhu; Ning Chen; Hugh Perkins; Bo Zhang
- Modeling Musical Influence with Topic ModelsAuthors: Uri Shalit; Daphna Weinshall; Gal Chechik
- Nested Chinese Restaurant Franchise Process: Applications to User Tracking and Document ModelingAuthors: Amr Ahmed; Liangjie Hong; Alexander Smola
- Parallel Markov Chain Monte Carlo for Nonparametric Mixture ModelsAuthors: Sinead Williamson; Avinava Dubey; Eric Xing
- MAD-Bayes: MAP-based Asymptotic Derivations from BayesAuthors: Tamara Broderick; Brian Kulis; Michael Jordan
- Topic Model Diagnostics: Assessing Domain Relevance via Topical AlignmentAuthors: Jason Chuang; Sonal Gupta; Christopher Manning; Jeffrey Heer

Track D: Statistical Learning and Inference

- Convex Relaxations for Learning Bounded-Treewidth Decomposable GraphsAuthors: Sesh Kumar K. S.; Francis Bach
- SVM for Learning with Label ProportionsAuthors: Felix Yu; Dong Liu; Sanjiv Kumar; Jebara Tony; Shih-Fu Chang
- Consistency of Online Random ForestsAuthors: Misha Denil; David Matheson; De Freitas Nando
- Relaxed expectation propagation based on l1-penalized KL minimizationAuthors: Yuan Qi; Yandong Guo
- A Fast and Exact Energy Minimization Algorithm for Cycle MRFsAuthors: Huayan Wang; Koller Daphne
- Approximate Inference in Collective Graphical ModelsAuthors: Daniel Sheldon; Tao Sun; Akshat Kumar; Tom Dietterich
- An Adaptive Learning Rate for Stochastic Variational InferenceAuthors: Rajesh Ranganath; Chong Wang; Blei David; Eric Xing
- The Bigraphical LassoAuthors: Alfredo Kalaitzis; John Lafferty; Neil Lawrence
- Anytime Representation LearningAuthors: Zhixiang Xu; Matt Kusner; Gao Huang; Kilian Weinberger
- Inference algorithms for pattern-based CRFs on sequence dataAuthors: Rustem Takhanov; Vladimir Kolmogorov

Deep Learning and Neuroscience

- On the importance of initialization and momentum in deep learningAuthors: Ilya Sutskever; James Martens; George Dahl; Geoffrey Hinton
- A non-IID Framework for Collaborative Filtering with Restricted Boltzmann MachinesAuthors: Kostadin Georgiev; Preslav Nakov
- Parsing epileptic events using a Markov switching process model for correlated time seriesAuthors: Drausin Wulsin; Emily Fox; Brian Litt
- Exploring the Mind: Integrating Questionnaires and fMRIAuthors: Esther Salazar; Ryan Bogdan; Adam Gorka; Ahmad Hariri; Lawrence Carin
- Gated Autoencoders with Tied Input WeightsAuthors: Alain Droniou; Olivier Sigaud
- Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted ImagesAuthors: Kyunghyun Cho
- Natural Image Bases to Represent Neuroimaging DataAuthors: Ashish Gupta; Murat Ayhan; Anthony Maida
- Direct Modeling of Complex Invariances for Visual Object FeaturesAuthors: Ka Yu Hui
- Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging SchemesAuthors: Ohad Shamir; Tong Zhang
- Optimal rates for stochastic convex optimization under Tsybakov noise conditionAuthors: Aaditya Ramdas; Aarti Singh
- Fast Semidifferential-based Submodular Function OptimizationAuthors: Rishabh Iyer; Stefanie Jegelka; Jeff Bilmes
- Composite Self-concordant MinimizationAuthors: Quoc Tran Dinh; Anastasios Kyrillidis; Volkan Cevher
- Mini-Batch Primal and Dual Methods for SVMsAuthors: Martin Takac; Avleen Bijral; Peter Richtarik; Nati Srebro
- Stochastic Alternating Direction Method of MultipliersAuthors: Hua Ouyang; Niao He; Long Tran; Alexander Gray
- Optimization with First-Order Surrogate FunctionsAuthors: Julien Mairal
- Fast Probabilistic Optimization from Noisy GradientsAuthors: Philipp Hennig

Compressed Sensing 3

- Spectral Compressed Sensing via Structured Matrix CompletionAuthors: Yuxin Chen; Yuejie Chi
- Sparse PCA through Low-rank ApproximationsAuthors: Dimitris Papailiopoulos; Alexandros Dimakis; Stavros Korokythakis
- Efficient Sparse Group Feature Selection via Nonconvex OptimizationAuthors: Shuo Xiang; Xiaotong Shen; Jieping Ye
- A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization ProblemsAuthors: Pinghua Gong; Changshui Zhang; Zhaosong Lu; Jianhua Huang; Jieping Ye
- Robust Sparse Regression under Adversarial CorruptionAuthors: Yudong Chen; Constantine Caramanis; Shie Mannor
- A Local Algorithm for Finding Well-Connected ClustersAuthors: Silvio Lattanzi; Vahab Mirrokni; Zeyuan Allen Zhu
- Monochromatic Bi-ClusteringAuthors: Sharon Wulff; Ruth Urner; Shai Ben-David
- Constrained fractional set programs and their application in local clustering and community detectionAuthors: Thomas B
- Graph Clustering: Big Clusters and Small ClustersAuthors: Yudong Chen; Nir Ailon; Huan Xu
- Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of ClusteringsAuthors: Nicola Rebagliati
- Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller SpaceAuthors: Javler Almingol ; Luis Montesano; Manuel Lopes
- Precision-recall space to correct external indices for biclusteringAuthors: Blaise Hanczar; Mohamed Nadif
- Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix CompletionAuthors: Jinfeng Yi; Rong Jin; Qi Qian; Anil Jain

Reinforcement Learning and Time Series

- ABC Reinforcement LearningAuthors: Christos Dimitrakakis; Nikolaos Tziortziotis
- Mean Reversion with a Variance ThresholdAuthors: Marco Cuturi; Alexandre d
- Gaussian Process Kernels for Pattern Discovery and ExtrapolationAuthors: Andrew Wilson; Ryan Adams
- Average Reward Optimization Objective In Partially Observable DomainsAuthors: Yuri Grinberg; Doina Precup
- Planning by Prioritized Sweeping with Small BackupsAuthors: Harm van Seijen; Rich Sutton
- Dynamic Covariance Models for Multivariate Financial Time SeriesAuthors: Yue Wu; Jose Miguel Hernandez-Lobato; Ghahramani Zoubin
- Learning Sparse Penalties for Change-point Detection using Max Margin Interval RegressionAuthors: Toby Hocking; Guillem Rigaill; Jean-Philippe VERT; Francis BACH
- Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule dataAuthors: Jan-Willem Van de Meent; Jonathan Bronson; Frank Wood; Ruben Gonzalez, Jr.; Chris Wiggins
- Learning Connections in Financial Time SeriesAuthors: Gartheeban Ganeshapillai; John Guttag; Andrew Lo
- The Extended Parameter Filter, Yusuf Bugra ErolAuthors: Lei Li; Bharath Ramsundar; Russell Stuart
- Transition Matrix Estimation in High Dimensional Time SeriesAuthors: Fang Han; Han Liu
- Track D: Learning Theory 1
- Margins, Shrinkage and BoostingAuthors: Matus Telgarsky
- Sharp Generalization Error Bounds for Randomly-projected ClassifiersAuthors: Robert Durrant; Ata Kaban
- Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output PredictionAuthors: S
- Collective Stability in Structured Prediction: Generalization from One ExampleAuthors: Ben London; Bert Huang; Ben Taskar; Lise Getoor
- Hierarchical Regularization Cascade for Joint LearningAuthors: Alon Zweig; Daphna Weinshall
- Learning Fair RepresentationsAuthors: Rich Zemel; Yu Wu; Kevin Swersky; Toniann Pitassi; Cynthia Dwork
- Differentially Private Learning with KernelsAuthors: Prateek Jain; Abhradeep Thakurta
- Rounding Methods for Discrete Linear ClassificationAuthors: Yann Chevaleyre; Frederick Koriche; Jean-Daniel Zucker

Topic Modeling 2

- Dependent Normalized Random MeasuresAuthors: Changyou Chen; Vinayak Rao; Yee Whye Teh; Wray Buntine
- Topic Discovery through Data Dependent and Random ProjectionsAuthors: Weicong Ding; Mohammad Hossein Rohban; Prakash Ishwar; Venkatesh Saligrama
- Factorial Multi-Task Learning : A Bayesian Nonparametric ApproachAuthors: Sunil Gupta; Dinh Phung; Svetha Venkatesh
- Scaling the Indian Buffet Process via Submodular MaximizationAuthors: Colorado Reed; Ghahramani Zoubin
- A Variational Approximation for Topic Modeling of Hierarchical CorporaAuthors: Do-kyum Kim; Geoffrey Voelker; Lawrence Saul
- Manifold Preserving Hierarchical Topic Models for Quantization and ApproximationAuthors: Minje Kim; Paris Smaragdis
- Subtle Topic Models and Discovering Subtly Manifested Software Concerns AutomaticallyAuthors: Mrinal Das; Suparna Bhattacharya; Chiranjib Bhattacharyya; Gopinath Kanchi
- Latent Dirichlet Allocation Topic Model with Soft Assignment of Descriptors to WordsAuthors: Daphna Weinshall; Gal Levi; Dmitri Hanukaev
- Efficient Multi-label Classification with Many LabelsAuthors: Wei Bi; James Kwok
- A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel LearningAuthors: Arash Afkanpour; Andras Gyorgy; Csaba Szepesvari; Michael Bowling

Track A: Invited Orals

- Beyond Label PropagationAuthors: Xiaojin (Jerry) Zhu, Zoubin Ghahramani, and John Lafferty
- Classic Paper Prize Talk: Online convex programming and generalized infinitesimal gradient ascent, ICML 2003Authors: Martin Zinkevich
- Learning Natural Language SemanticsAuthors: Percy Liang
- Machine Learning CompetitionsAuthors: Ben Hamner
- Large-Scale Bandit Problems and KWIK Learning,Authors: Jacob Abernethy; Kareem Amin; Michael Kearns; Moez Draief

Track A: Online Learning 1

- Online Kernel Learning with a Near Optimal Sparsity BoundAuthors: Lijun Zhang; Rong Jin; Xiaofei He
- On the Generalization Ability of Online Learning Algorithms for Pairwise Loss FunctionsAuthors: Prateek Jain; Bharath Sriperumbudur; Purushottam Kar; Harish Karnick
- Thompson Sampling for Contextual Bandits with Linear PayoffsAuthors: Shipra Agrawal; Navin Goyal
- Online Learning under Delayed FeedbackAuthors: Pooria Joulani; Andras Gyorgy; Csaba Szepesvari
- Almost Optimal Exploration in Multi-Armed BanditsAuthors: Zohar Karnin; Tomer Koren; Oren Somekh

Track A: Dimensionality Reduction and Semi-Supervised Learning

- Squared-loss Mutual Information RegularizationAuthors: Gang Niu; Wittawat Jitkrittum; Bo Dai, ; Hirotaka Hachiya; Masashi Sugiyama
- Ellipsoidal Multiple Instance LearningAuthors: Gabriel Krummenacher; Cheng Soon Ong; Joachim Buhmann
- Infinitesimal Annealing for Training Semi-Supervised Support Vector MachineAuthors: Kohei Ogawa; Motoki Imamura; Ichiro Takeuchi; Masashi Sugiyama
- Sparse Gaussian Conditional Random Fields: Algorithms, and Application to Energy ForecastingAuthors: Matt Wytock; Zico Kolter
- Adaptive Hamiltonian and Riemann Manifold Monte Carlo SamplersAuthors: Ziyu Wang; Shakir Mohamed; Nando de Freitas

Session

Track B: Feature Learning

- Forecastable Component AnalysisAuthors: Georg Goerg
- Multi-View Clustering and Feature Learning via Structured SparsityAuthors: Hua Wang; Feiping Nie; Heng Huang
- Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain AdaptationAuthors: Boqing Gong; Kristen Grauman; Fei Sha
- On Nonlinear Generalization of Sparse Coding and Dictionary LearningAuthors: Jeffrey Ho; Yuchen Xie; Baba Vemuri
- Feature Multi-Selection among Subjective FeaturesAuthors: Sivan Sabato; Adam Kalai
- Sparsity-Based Generalization Bounds for Predictive Sparse CodingAuthors: Nishant Mehta; Alexander Gray
- A Unified Robust Regression Model for Lasso-like AlgorithmsAuthors: Wenzhuo Yang; Huan Xu

Track B: Optimization and Integration

- Stochastic Simultaneous Optimistic OptimizationAuthors: Michal Valko; Alexandra Carpentier; Remi Munos
- Block-Coordinate Frank-Wolfe Optimization for Structural SVMs,Authors: Simon Lacoste-Julien; Martin Jaggi; Mark Schmidt; Patrick Pletscher
- Taming the Curse of Dimensionality: Discrete Integration by Hashing and OptimizationAuthors: Stefano Ermon; Carla Gomes; Ashish Sabharwal; Bart Selman
- Expensive Function Optimization with Stochastic Binary OutcomesAuthors: Matthew Tesch; Howie Choset; Jeff Schneider
- O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex FunctionsAuthors: Lijun Zhang; Tianbao Yang; Rong Jin; Xiaofei He
- Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization,Authors: Martin Jaggi
- Algorithms for Direct 0-1 Loss Optimization in Binary ClassificationAuthors: Tan Nguyen; Scott Sanner
- Local Deep Kernel Learning for Efficient Non-Linear SVM PreDictionAuthors: Cijo Jose; Prasoon Goyal; Parv Aggrwal; Manik Varma

Tutorials

- Tensor Decomposition Algorithms for Latent Variable Model EstimationAuthors:Anima Anandkumar, Daniel Hsu, Sham M Kakade
- Copulas in Machine LearningAuthors: Gal Elidan
- Deep LearningAuthors: Yann LeCun, Marc Aurelio Anzato
- Topological Data Analysis Part IAuthors: Primoz Skraba, Sayan Mukherjee
- Multi-Target PredictionAuthors: Willem Wargman, Krysztof Dembczybski, Eyke Hullermeier
- Submodularity in Machine Learning: New Directions Part IAuthors: Andreas Krause, Stefanie Jegelka
- Discovering Multiple Clustering Solutions: Grouping Objects in Different ViewsAuthors: Emmanuel Muller, Stephan Gunnemann, Ines Farber, Thomas Seidl
- Copulas in Machine LearningAuthors: Gal Elidan
- Energy Based Unsupervised LearningAuthors:
- Topological Data Analysis Part IIAuthors: Primoz Skraba and Sayan Mukherjee
- Music Information Research Based on Machine LearningAuthors: Masataka Goto and Kazuyoshi Yoshii
- Submodularity in Machine Learning: New Directions Part IIAuthors: Andreas Krause, Stefanie Jegelka

Track C: General SVM and Decision Tree Methods

- Multi-Class Classification with Maximum Margin Multiple KernelAuthors: Corinna Cortes; Mehryar Mohri; Afshin Rostamizadeh
- Top-down particle filtering for Bayesian decision treesAuthors: Balaji Lakshminarayanan; Daniel Roy; Yee Whye Teh
- Cost-Sensitive Tree of ClassifiersAuthors: Zhixiang Xu; Matt Kusner; Kilian Weinberger; Minmin Chen
- On the Statistical Consistency of Algorithms for Binary Classification under Class ImbalanceAuthors: Aditya Menon; Harikrishna Narasimhan; Shivani Agarwal; Sanjay Chawla
- Quickly Boosting Decision Trees - Pruning Underachieving Features EarlyAuthors: Ron Appel; Thomas Fuchs; Piotr Dollar; Pietro Perona
- Tree-Independent Dual-Tree AlgorithmsAuthors: Ryan Curtin; William March; Parikshit Ram; David Anderson; Alexander Gray; Charles Isbell
- Loss-Proportional Subsampling for Subsequent ERMAuthors: Paul Mineiro; Nikos Karampatziakis
- Saving Evaluation Time for the Decision Function in Boosting: Representation and Reordering Base LearnerAuthors: Peng Sun; Jie Zhou
- Safe Screening of Non-Support Vectors in Pathwise SVM ComputationAuthors: Kohei Ogawa; Yoshiki Suzuki; Ichiro Takeuchi
- Convex formulations of radius-margin based Support Vector MachinesAuthors: Huyen Do; Alexandros Kalousis
- The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear ClassificationAuthors: Ofir Pele; Ben Taskar; Amir Globerson; Michael Werman

Track C: Vision

- An Optimal Policy for Target Localization with Application to Electron MicroscopyAuthors: Raphael Sznitman; Aurelien Lucchi; Peter Frazier; Bruno Jedynak; Pascal Fua
- Fast Image TaggingAuthors: Minmin Chen; Alice Zheng; Kilian Weinberger
- An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source SeparationAuthors: Nicholas Bryan; Gautham Mysore
- Max-Margin Multiple-Instance Dictionary LearningAuthors: Xinggang Wang; Baoyuan Wang; Xiang Bai; Wenyu Liu; Zhuowen Tu
- Parameter Learning and Convergent Inference for Dense Random FieldsAuthors: Philipp Kraehenbuehl; Vladlen Koltun
- Robust and Discriminative Self-Taught LearningAuthors: Hua Wang; Feiping Nie; Heng Huang
- Learning Spatio-Temporal Structure from RGB-D Videos for Human Activity Detection and AnticipationAuthors: Hema Koppula; Ashutosh Saxena
- A Spectral Learning Approach to Range-Only SLAMAuthors: Byron Boots; Geoff Gordon
- Non-Linear Stationary Subspace Analysis with Application to Video ClassificationAuthors: Mahsa Baktashmotlagh; Mehrtash Harandi; Abbas Bigdeli; Brian Lovell; Mathieu Salzmann
- On Compact Codes for Spatially Pooled FeaturesAuthors: Yangqing Jia; Oriol Vinyals; Trevor Darrell
- Analogy-preserving Semantic Embedding for Visual Object CategorizationAuthors: Sung Ju Hwang; Kristen Grauman; Fei Sha

Track D: Spectral Learning and Tensors

- Spectral Learning of Hidden Markov Models from Dynamic and Static DataAuthors: Tzu-Kuo Huang; Jeff Schneider
- Spectral Experts for Estimating Mixtures of Linear RegressionsAuthors: Arun Tejasvi Chaganty; Percy Liang
- Learning Linear Bayesian Networks with Latent Variables,Authors: Animashree Anandkumar; Daniel Hsu; Adel Javanmard; Sham Kakade
- On learning parametric-output HMMsAuthors: Aryeh Kontorovich; Boaz Nadler; Roi Weiss
- Tensor Analyzers, Yichuan Tang; Ruslan SalakhutdinovAuthors: Geoffrey Hinton
- Unfolding Latent Tree Structures using 4th Order TensorsAuthors: Mariya Ishteva; Haesun Park; Le Song
- Infinite Positive Semidefinite Tensor Factorization with Application to Music Signal AnalysisAuthors: Kazuyoshi Yoshii; Ryota Tomioka; Daichi Mochihashi; Masataka Goto

Track D: Learning Theory II

- Exploiting Ontology Structures and Unlabeled Data for Learning,Authors: Maria-Florina Balcan; Avrim Blum; Yishay Mansour
- One-Pass AUC OptimizationAuthors: Wei Gao; Rong Jin; Shenghuo Zhu; Zhi-Hua Zhou
- Near-Optimal Bounds for Cross-Validation via Loss StabilityAuthors: Ravi Kumar; Daniel Lokshtanov; Sergei Vassilvitskii; Andrea Vattani
- Algebraic Classifiers: generic parallel training, online training, and fast cross-validationAuthors: Michael Izbicki
- Top-k Selection based on Adaptive Sampling of Noisy Preferences,Authors: Robert Busa-Fekete; Balazs Szorenyi; Paul Weng; Weiwei Cheng; Eyke Hullermeier
- Enhanced statistical rankings via targeted data collectionAuthors: Braxton Osting; Christoph Brune; Stanley Osher
- Efficient Ranking from Pairwise ComparisonsAuthors: Fabian Wauthier; Michael Jordan; Nebojsa Jojic
- Stable Coactive Learning via PerturbationAuthors: Karthik Raman; Thorsten Joachims,; Pannaga Shivaswamy; Tobias Schnabel

Image Credit: NASA/JPL/Space Science Institute

Full-Res: W00083229.jpg

W00083229.jpg was taken on July 20, 2013 and received on Earth July 20, 2013. The camera was pointing toward SATURN-ERING at approximately 623,956 miles (1,004,160 kilometers) away, and the image was taken using the CL1 and GRN filters. This image has not been validated or calibrated.

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