Conferences in DBLP
Douglas Aberdeen , Jonathan Baxter Scalable Internal-State Policy-Gradient Methods for POMDPs. [Citation Graph (0, 0)][DBLP ] Conf ] Érick Alphonse , Stan Matwin Feature Subset Selection and Inductive Logic Programming. [Citation Graph (0, 0)][DBLP ] Conf ] Valentina Bayer Zubek , Thomas G. Dietterich Pruning Improves Heuristic Search for Cost-Sensitive Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Sugato Basu , Arindam Banerjee , Raymond J. Mooney Semi-supervised Clustering by Seeding. [Citation Graph (0, 0)][DBLP ] Conf ] Jacques Ales Bianchetti , Céline Rouveirol , Michèle Sebag Constraint-based Learning of Long Relational Concepts. [Citation Graph (0, 0)][DBLP ] Conf ] Joseph Bockhorst , Mark Craven Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data. [Citation Graph (0, 0)][DBLP ] Conf ] Blai Bonet An epsilon-Optimal Grid-Based Algorithm for Partially Observable Markov Decision Processes. [Citation Graph (0, 0)][DBLP ] Conf ] Björn Bringmann , Stefan Kramer , Friedrich Neubarth , Hannes Pirker , Gerhard Widmer Transformation-Based Regression. [Citation Graph (0, 0)][DBLP ] Conf ] Zheng Chen , Liu Wenyin , Feng Zhang A New Statistical Approach to Personal Name Extraction. [Citation Graph (0, 0)][DBLP ] Conf ] Michael Chisholm , Prasad Tadepalli Learning Decision Rules by Randomized Iterative Local Search. [Citation Graph (0, 0)][DBLP ] Conf ] Elisabeth Crawford , Judy Kay , Eric McCreath IEMS - The Intelligent Email Sorter. [Citation Graph (0, 0)][DBLP ] Conf ] Denver Dash , Gregory F. Cooper Exact model averaging with naive Bayesian classifiers. [Citation Graph (0, 0)][DBLP ] Conf ] Dennis DeCoste Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry. [Citation Graph (0, 0)][DBLP ] Conf ] Thomas G. Dietterich , Dídac Busquets , Ramon López de Mántaras , Carles Sierra Action Refinement in Reinforcement Learning by Probability Smoothing. [Citation Graph (0, 0)][DBLP ] Conf ] Kurt Driessens , Saso Dzeroski Integrating Experimentation and Guidance in Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Saso Dzeroski , Bernard Zenko Is Combining Classifiers Better than Selecting the Best One. [Citation Graph (0, 0)][DBLP ] Conf ] Tapio Elomaa , Juho Rousu Fast Minimum Training Error Discretization. [Citation Graph (0, 0)][DBLP ] Conf ] César Ferri , Peter A. Flach , José Hernández-Orallo Learning Decision Trees Using the Area Under the ROC Curve. [Citation Graph (0, 0)][DBLP ] Conf ] Leigh J. Fitzgibbon , David L. Dowe , Lloyd Allison Univariate Polynomial Inference by Monte Carlo Message Length Approximation. [Citation Graph (0, 0)][DBLP ] Conf ] Joao Gama An Analysis of Functional Trees. [Citation Graph (0, 0)][DBLP ] Conf ] Dragan Gamberger , Nada Lavrac Descriptive Induction through Subgroup Discovery: A Case Study in a Medical Domain. [Citation Graph (0, 0)][DBLP ] Conf ] Ashutosh Garg , Sariel Har-Peled , Dan Roth On generalization bounds, projection profile, and margin distribution. [Citation Graph (0, 0)][DBLP ] Conf ] Thomas Gärtner , Peter A. Flach , Adam Kowalczyk , Alex J. Smola Multi-Instance Kernels. [Citation Graph (0, 0)][DBLP ] Conf ] Rayid Ghani Combining Labeled and Unlabeled Data for MultiClass Text Categorization. [Citation Graph (0, 0)][DBLP ] Conf ] Mohammad Ghavamzadeh , Sridhar Mahadevan Hierarchically Optimal Average Reward Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Amir Globerson , Naftali Tishby Sufficient Dimensionality Reduction - A novel Analysis Method. [Citation Graph (0, 0)][DBLP ] Conf ] Michael Goebel , Patricia J. Riddle , Mike Barley A Unified Decomposition of Ensemble Loss for Predicting Ensemble Performance. [Citation Graph (0, 0)][DBLP ] Conf ] Jesus A. Gonzalez , Lawrence B. Holder , Diane J. Cook Graph-Based Relational Concept Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Carlos Guestrin , Michail G. Lagoudakis , Ronald Parr Coordinated Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Carlos Guestrin , Relu Patrascu , Dale Schuurmans Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs. [Citation Graph (0, 0)][DBLP ] Conf ] Bernhard Hengst Discovering Hierarchy in Reinforcement Learning with HEXQ. [Citation Graph (0, 0)][DBLP ] Conf ] Colin K. M. Ho Classification Value Grouping. [Citation Graph (0, 0)][DBLP ] Conf ] David Jensen , Jennifer Neville Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Sham Kakade , John Langford Approximately Optimal Approximate Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Sham Kakade , Yee Whye Teh , Sam T. Roweis An Alternate Objective Function for Markovian Fields. [Citation Graph (0, 0)][DBLP ] Conf ] Sepandar D. Kamvar , Dan Klein , Christopher D. Manning Interpreting and Extending Classical Agglomerative Clustering Algorithms using a Model-Based approach. [Citation Graph (0, 0)][DBLP ] Conf ] Hisashi Kashima , Teruo Koyanagi Kernels for Semi-Structured Data. [Citation Graph (0, 0)][DBLP ] Conf ] S. Sathiya Keerthi , Kaibo Duan , Shirish Krishnaj Shevade , Aun Neow Poo A Fast Dual Algorithm for Kernel Logistic Regression. [Citation Graph (0, 0)][DBLP ] Conf ] Dan Klein , Sepandar D. Kamvar , Christopher D. Manning From Instance-level Constraints to Space-Level Constraints: Making the Most of Prior Knowledge in Data Clustering. [Citation Graph (0, 0)][DBLP ] Conf ] Risi Imre Kondor , John D. Lafferty Diffusion Kernels on Graphs and Other Discrete Input Spaces. [Citation Graph (0, 0)][DBLP ] Conf ] Gert R. G. Lanckriet , Nello Cristianini , Peter L. Bartlett , Laurent El Ghaoui , Michael I. Jordan Learning the Kernel Matrix with Semi-Definite Programming. [Citation Graph (0, 0)][DBLP ] Conf ] John Langford Combining Trainig Set and Test Set Bounds. [Citation Graph (0, 0)][DBLP ] Conf ] John Langford , Martin Zinkevich , Sham Kakade Competitive Analysis of the Explore/Exploit Tradeoff. [Citation Graph (0, 0)][DBLP ] Conf ] Pat Langley , Javier Nicolás Sánchez , Ljupco Todorovski , Saso Dzeroski Inducing Process Models from Continuous Data. [Citation Graph (0, 0)][DBLP ] Conf ] Adam Laud , Gerald DeJong Reinforcement Learning and Shaping: Encouraging Intended Behaviors. [Citation Graph (0, 0)][DBLP ] Conf ] Guy Lebanon , John D. Lafferty Cranking: Combining Rankings Using Conditional Probability Models on Permutations. [Citation Graph (0, 0)][DBLP ] Conf ] Christopher Leckie , Kotagiri Ramamohanarao Learning to Share Distributed Probabilistic Beliefs. [Citation Graph (0, 0)][DBLP ] Conf ] Yaoyong Li , Hugo Zaragoza , Ralf Herbrich , John Shawe-Taylor , Jaz S. Kandola The Perceptron Algorithm with Uneven Margins. [Citation Graph (0, 0)][DBLP ] Conf ] Bing Liu , Wee Sun Lee , Philip S. Yu , Xiaoli Li Partially Supervised Classification of Text Documents. [Citation Graph (0, 0)][DBLP ] Conf ] Huan Liu , Hiroshi Motoda , Lei Yu Feature Selection with Selective Sampling. [Citation Graph (0, 0)][DBLP ] Conf ] Fletcher Lu , Relu Patrascu , Dale Schuurmans Investigating the Maximum Likelihood Alternative to TD(lambda). [Citation Graph (0, 0)][DBLP ] Conf ] Artur Merke , Ralf Schoknecht A Necessary Condition of Convergence for Reinforcement Learning with Function Approximation. [Citation Graph (0, 0)][DBLP ] Conf ] Carsten Meyer , Peter Beyerlein Towards "Large Margin" Speech Recognizers by Boosting and Discriminative Training. [Citation Graph (0, 0)][DBLP ] Conf ] Dunja Mladenic Learning word normalization using word suffix and context from unlabeled data. [Citation Graph (0, 0)][DBLP ] Conf ] Ion Muslea , Steven Minton , Craig A. Knoblock Active + Semi-supervised Learning = Robust Multi-View Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Ion Muslea , Steven Minton , Craig A. Knoblock Adaptive View Validation: A First Step Towards Automatic View Detection. [Citation Graph (0, 0)][DBLP ] Conf ] Jangmin O , Jae Won Lee , Byoung-Tak Zhang Stock Trading System Using Reinforcement Learning with Cooperative Agents. [Citation Graph (0, 0)][DBLP ] Conf ] Tim Oates , Devina Desai , Vinay Bhat Learning k-Reversible Context-Free Grammars from Positive Structural Examples. [Citation Graph (0, 0)][DBLP ] Conf ] Nuria Oliver , Ashutosh Garg MMIHMM: Maximum Mutual Information Hidden Markov Models. [Citation Graph (0, 0)][DBLP ] Conf ] Anand Panangadan , Michael G. Dyer Learning Spatial and Temporal Correlation for Navigation in a 2-Dimensional Continuous World. [Citation Graph (0, 0)][DBLP ] Conf ] Seong-Bae Park , Byoung-Tak Zhang A Boosted Maximum Entropy Model for Learning Text Chunking. [Citation Graph (0, 0)][DBLP ] Conf ] Theodore J. Perkins , Mark D. Pendrith On the Existence of Fixed Points for Q-Learning and Sarsa in Partially Observable Domains. [Citation Graph (0, 0)][DBLP ] Conf ] Leonid Peshkin , Christian R. Shelton Learning from Scarce Experience. [Citation Graph (0, 0)][DBLP ] Conf ] Marc Pickett , Andrew G. Barto PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Bhavani Raskutti , Herman L. Ferrá , Adam Kowalczyk Using Unlabelled Data for Text Classification through Addition of Cluster Parameters. [Citation Graph (0, 0)][DBLP ] Conf ] Malcolm R. K. Ryan Using Abstract Models of Behaviours to Automatically Generate Reinforcement Learning Hierarchies. [Citation Graph (0, 0)][DBLP ] Conf ] Craig Saunders , Hauke Tschach , John Shawe-Taylor Syllables and other String Kernel Extensions. [Citation Graph (0, 0)][DBLP ] Conf ] Robert E. Schapire , Marie Rochery , Mazin G. Rahim , Narendra Gupta Incorporating Prior Knowledge into Boosting. [Citation Graph (0, 0)][DBLP ] Conf ] Robert E. Schapire , Peter Stone , David A. McAllester , Michael L. Littman , János A. Csirik Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation. [Citation Graph (0, 0)][DBLP ] Conf ] Alexander K. Seewald How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness. [Citation Graph (0, 0)][DBLP ] Conf ] Sandeep Seri , Prasad Tadepalli Model-based Hierarchical Average-reward Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Daniel G. Shapiro , Pat Langley Separating Skills from Preference: Using Learning to Program by Reward. [Citation Graph (0, 0)][DBLP ] Conf ] Noam Slonim , Gill Bejerano , Shai Fine , Naftali Tishby Discriminative Feature Selection via Multiclass Variable Memory Markov Model. [Citation Graph (0, 0)][DBLP ] Conf ] David Stirling Learning to Fly by Controlling Dynamic Instabilities. [Citation Graph (0, 0)][DBLP ] Conf ] David J. Stracuzzi , Paul E. Utgoff Randomized Variable Elimination. [Citation Graph (0, 0)][DBLP ] Conf ] Malcolm J. A. Strens , Mark Bernhardt , Nicholas Everett Markov Chain Monte Carlo Sampling using Direct Search Optimization. [Citation Graph (0, 0)][DBLP ] Conf ] Dorian Suc , Ivan Bratko Qualitative reverse engineering. [Citation Graph (0, 0)][DBLP ] Conf ] Fumio Takechi , Einoshin Suzuki Finding an Optimal Gain-Ratio Subset-Split Test for a Set-Valued Attribute in Decision Tree Induction. [Citation Graph (0, 0)][DBLP ] Conf ] Loo-Nin Teow , Haifeng Liu , Hwee Tou Ng , Eric Yap Refining the Wrapper Approach - Smoothed Error Estimates for Feature Selection. [Citation Graph (0, 0)][DBLP ] Conf ] Shien-Shin Tham , Arnaud Doucet , Kotagiri Ramamohanarao Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo. [Citation Graph (0, 0)][DBLP ] Conf ] Kai Ming Ting Issues in Classifier Evaluation using Optimal Cost Curves. [Citation Graph (0, 0)][DBLP ] Conf ] Yong Wang , Ian H. Witten Modeling for Optimal Probability Prediction. [Citation Graph (0, 0)][DBLP ] Conf ] Xindong Wu , Chengqi Zhang , Shichao Zhang Mining Both Positive and Negative Association Rules. [Citation Graph (0, 0)][DBLP ] Conf ] Ying Yang , Geoffrey I. Webb Non-Disjoint Discretization for Naive-Bayes Classifiers. [Citation Graph (0, 0)][DBLP ] Conf ] Huajie Zhang , Charles X. Ling Representational Upper Bounds of Bayesian Networks. [Citation Graph (0, 0)][DBLP ] Conf ] Qi Zhang , Sally A. Goldman , Wei Yu , Jason E. Fritts Content-Based Image Retrieval Using Multiple-Instance Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Tong Zhang Statistical Behavior and Consistency of Support Vector Machines, Boosting, and Beyond. [Citation Graph (0, 0)][DBLP ] Conf ] 