Conferences in DBLP
Naoki Abe , Philip M. Long Associative Reinforcement Learning using Linear Probabilistic Concepts. [Citation Graph (0, 0)][DBLP ] Conf ] Naoki Abe , Atsuyoshi Nakamura Learning to Optimally Schedule Internet Banner Advertisements. [Citation Graph (0, 0)][DBLP ] Conf ] Enrico Blanzieri , Francesco Ricci A Minimum Risk Metric for Nearest Neighbor Classification. [Citation Graph (0, 0)][DBLP ] Conf ] Gianluca Bontempi , Mauro Birattari , Hugues Bersini Local Learning for Iterated Time-Series Prediction. [Citation Graph (0, 0)][DBLP ] Conf ] Antal van den Bosch Instance-Family Abstraction in Memory-Based Language Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Justin A. Boyan Least-Squares Temporal Difference Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Mark Brodie , Gerald DeJong Learning to Ride a Bicycle using Iterated Phantom Induction. [Citation Graph (0, 0)][DBLP ] Conf ] Wolfram Burgard , Dieter Fox , Hauke Jans , Christian Matenar , Sebastian Thrun Sonar-Based Mapping of Large-Scale Mobile Robot Environments using EM. [Citation Graph (0, 0)][DBLP ] Conf ] Igor V. Cadez , Christine E. McLaren , Padhraic Smyth , Geoffrey J. McLachlan Hierarchical Models for Screening of Iron Deficiency Anemia. [Citation Graph (0, 0)][DBLP ] Conf ] Claire Cardie , Scott Mardis , David R. Pierce Combining Error-Driven Pruning and Classification for Partial Parsing. [Citation Graph (0, 0)][DBLP ] Conf ] Wei Fan , Salvatore J. Stolfo , Junxin Zhang , Philip K. Chan AdaCost: Misclassification Cost-Sensitive Boosting. [Citation Graph (0, 0)][DBLP ] Conf ] Laura Firoiu , Paul R. Cohen Abstracting from Robot Sensor Data using Hidden Markov Models. [Citation Graph (0, 0)][DBLP ] Conf ] Eibe Frank , Ian H. Witten Making Better Use of Global Discretization. [Citation Graph (0, 0)][DBLP ] Conf ] Yoav Freund , Llew Mason The Alternating Decision Tree Learning Algorithm. [Citation Graph (0, 0)][DBLP ] Conf ] Joao Gama Discriminant Trees. [Citation Graph (0, 0)][DBLP ] Conf ] Dragan Gamberger , Nada Lavrac , Ciril Groselj Experiments with Noise Filtering in a Medical Domain. [Citation Graph (0, 0)][DBLP ] Conf ] Melinda T. Gervasio , Wayne Iba , Pat Langley Learning User Evaluation Functions for Adaptive Scheduling Assistance. [Citation Graph (0, 0)][DBLP ] Conf ] Attilio Giordana , Roberto Piola On Some Misbehaviour of Back-Propagation with Non-Normalized RBFNs and a Solution. [Citation Graph (0, 0)][DBLP ] Conf ] Michael Bonnell Harries Boosting a Strong Learner: Evidence Against the Minimum Margin. [Citation Graph (0, 0)][DBLP ] Conf ] Yuh-Jyh Hu , Suzanne B. Sandmeyer , Dennis F. Kibler Detecting Motifs from Sequences. [Citation Graph (0, 0)][DBLP ] Conf ] Daisuke Iijima , Wenwei Yu , Hiroshi Yokoi , Yukinori Kakazu Distributed Robotic Learning: Adaptive Behavior Acquisition for Distributed Autonomous Swimming Robot in Real World. [Citation Graph (0, 0)][DBLP ] Conf ] Thorsten Joachims Transductive Inference for Text Classification using Support Vector Machines. [Citation Graph (0, 0)][DBLP ] Conf ] Hajime Kimura , Shigenobu Kobayashi Efficient Non-Linear Control by Combining Q-learning with Local Linear Controllers. [Citation Graph (0, 0)][DBLP ] Conf ] Pat Langley , Stephanie Sage Tractable Average-Case Analysis of Naive Bayesian Classifiers. [Citation Graph (0, 0)][DBLP ] Conf ] Michael van Lent , John E. Laird Learning Hierarchical Performance Knowledge by Observation. [Citation Graph (0, 0)][DBLP ] Conf ] Choh-Man Teng Correcting Noisy Data. [Citation Graph (0, 0)][DBLP ] Conf ] Marina Meila An Accelerated Chow and Liu Algorithm: Fitting Tree Distributions to High-Dimensional Sparse Data. [Citation Graph (0, 0)][DBLP ] Conf ] Dunja Mladenic , Marko Grobelnik Feature Selection for Unbalanced Class Distribution and Naive Bayes. [Citation Graph (0, 0)][DBLP ] Conf ] Katharina Morik , Peter Brockhausen , Thorsten Joachims Combining Statistical Learning with a Knowledge-Based Approach - A Case Study in Intensive Care Monitoring. [Citation Graph (0, 0)][DBLP ] Conf ] Andrew Y. Ng , Daishi Harada , Stuart J. Russell Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. [Citation Graph (0, 0)][DBLP ] Conf ] Maziar Palhang , Arcot Sowmya Learning Discriminatory and Descriptive Rules by an Inductive Logic Programming System. [Citation Graph (0, 0)][DBLP ] Conf ] Rajesh Parekh , Vasant Honavar Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples. [Citation Graph (0, 0)][DBLP ] Conf ] Leonid Peshkin , Nicolas Meuleau , Leslie Pack Kaelbling Learning Policies with External Memory. [Citation Graph (0, 0)][DBLP ] Conf ] Uros Pompe Noise-Tolerant Recursive Best-First Induction. [Citation Graph (0, 0)][DBLP ] Conf ] Bob Price , Craig Boutilier Implicit Imitation in Multiagent Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Jason Rennie , Andrew McCallum Using Reinforcement Learning to Spider the Web Efficiently. [Citation Graph (0, 0)][DBLP ] Conf ] Marko Robnik-Sikonja , Igor Kononenko Attribute Dependencies, Understandability and Split Selection in Tree Based Models. [Citation Graph (0, 0)][DBLP ] Conf ] Yasubumi Sakakibara , Mitsuhiro Kondo GA-based Learning of Context-Free Grammars using Tabular Representations. [Citation Graph (0, 0)][DBLP ] Conf ] Tobias Scheffer , Thorsten Joachims Expected Error Analysis for Model Selection. [Citation Graph (0, 0)][DBLP ] Conf ] Jeff G. Schneider , Weng-Keen Wong , Andrew W. Moore , Martin A. Riedmiller Distributed Value Functions. [Citation Graph (0, 0)][DBLP ] Conf ] Sam Scott , Stan Matwin Feature Engineering for Text Classification. [Citation Graph (0, 0)][DBLP ] Conf ] Luis Talavera Feature Selection as a Preprocessing Step for Hierarchical Clustering. [Citation Graph (0, 0)][DBLP ] Conf ] Douglas A. Talbert , Douglas H. Fisher OPT-KD: An Algorithm for Optimizing Kd-Trees. [Citation Graph (0, 0)][DBLP ] Conf ] Cynthia A. Thompson , Mary Elaine Califf , Raymond J. Mooney Active Learning for Natural Language Parsing and Information Extraction. [Citation Graph (0, 0)][DBLP ] Conf ] Sebastian Thrun , John Langford , Dieter Fox Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes. [Citation Graph (0, 0)][DBLP ] Conf ] Paul E. Utgoff , David J. Stracuzzi Approximation Via Value Unification. [Citation Graph (0, 0)][DBLP ] Conf ] Shivakumar Vaithyanathan , Byron Dom Model Selection in Unsupervised Learning with Applications To Document Clustering. [Citation Graph (0, 0)][DBLP ] Conf ] Volodya Vovk , Alexander Gammerman , Craig Saunders Machine-Learning Applications of Algorithmic Randomness. [Citation Graph (0, 0)][DBLP ] Conf ] Mohammed Waleed Kadous Learning Comprehensible Descriptions of Multivariate Time Series. [Citation Graph (0, 0)][DBLP ] Conf ] Gang Wang , Sridhar Mahadevan Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes. [Citation Graph (0, 0)][DBLP ] Conf ] Donghui Wu , Kristin P. Bennett , Nello Cristianini , John Shawe-Taylor Large Margin Trees for Induction and Transduction. [Citation Graph (0, 0)][DBLP ] Conf ] Wei Zhang An Region-Based Learning Approach to Discovering Temporal Structures in Data. [Citation Graph (0, 0)][DBLP ] Conf ] Zijian Zheng , Geoffrey I. Webb , Kai Ming Ting Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees. [Citation Graph (0, 0)][DBLP ] Conf ] Yuanhui Zhou , Carla E. Brodley A Hybrid Lazy-Eager Approach to Reducing the Computation and Memory Requirements of Local Parametric Learning Algorithms. [Citation Graph (0, 0)][DBLP ] Conf ] 