Proceedings of the 12th International Conference on Machine Learning
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
EDIT!
CC-BY
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter

Armand Prieditis, Stuart J. Russell
Proceedings of the 12th International Conference on Machine Learning
ICML, 1995.

KER
DBLP
Scholar
Full names Links ISxN
@proceedings{ICML-1995,
	address       = "Tahoe City, California, USA",
	editor        = "Armand Prieditis and Stuart J. Russell",
	isbn          = "1-55860-377-8",
	publisher     = "{Morgan Kaufmann}",
	title         = "{Proceedings of the 12th International Conference on Machine Learning}",
	year          = 1995,
}

Contents (71 items)

ICML-1995-AbeLN #2d #algorithm #learning #online #using
On-line Learning of Binary Lexical Relations Using Two-dimensional Weighted Majority Algorithms (NA, HL, AN), pp. 3–11.
ICML-1995-AlmuallimAK #learning #on the
On Handling Tree-Structured Attributed in Decision Tree Learning (HA, YA, SK), pp. 12–20.
ICML-1995-AuerHM #theory and practice
Theory and Applications of Agnostic PAC-Learning with Small Decision Trees (PA, RCH, WM), pp. 21–29.
ICML-1995-Baird #algorithm #approximate #learning
Residual Algorithms: Reinforcement Learning with Function Approximation (LCBI), pp. 30–37.
ICML-1995-BalujaC #algorithm #search-based #standard
Removing the Genetics from the Standard Genetic Algorithm (SB, RC), pp. 38–46.
ICML-1995-Benson #induction #learning #modelling
Inductive Learning of Reactive Action Models (SB), pp. 47–54.
ICML-1995-BlackmoreM #grid #incremental #network #visualisation
Visualizing High-Dimensional Structure with the Incremental Grid Growing Neural Network (JB, RM), pp. 55–63.
ICML-1995-Blum #algorithm #empirical #scheduling
Empirical Support for Winnow and Weighted-Majority Based Algorithms: Results on a Calendar Scheduling Domain (AB), pp. 64–72.
ICML-1995-Brodley #automation
Automatic Selection of Split Criterion during Tree Growing Based on Node Location (CEB), pp. 73–80.
ICML-1995-BrunkP #bias #semantics
A Lexical Based Semantic Bias for Theory Revision (CB, MJP), pp. 81–89.
ICML-1995-ChanS #comparative #evaluation
A Comparative Evaluation of Voting and Meta-learning on Partitioned Data (PKC, SJS), pp. 90–98.
ICML-1995-CichoszM #difference #learning #performance
Fast and Efficient Reinforcement Learning with Truncated Temporal Differences (PC, JJM), pp. 99–107.
ICML-1995-ClearyT #distance #using
K*: An Instance-based Learner Using and Entropic Distance Measure (JGC, LET), pp. 108–114.
ICML-1995-Cohen #effectiveness #induction #performance
Fast Effective Rule Induction (WWC), pp. 115–123.
ICML-1995-Cohen95a #categorisation #learning #relational
Text Categorization and Relational Learning (WWC), pp. 124–132.
ICML-1995-CrawH #network #refinement
Protein Folding: Symbolic Refinement Competes with Neural Networks (SC, PH), pp. 133–141.
ICML-1995-Cussens #algorithm #analysis #finite #learning
A Bayesian Analysis of Algorithms for Learning Finite Functions (JC), pp. 142–149.
ICML-1995-DaganE #classification #probability
Committee-Based Sampling For Training Probabilistic Classifiers (ID, SPE), pp. 150–157.
ICML-1995-DattaK #concept #learning #prototype
Learning Prototypical Concept Descriptions (PD, DFK), pp. 158–166.
ICML-1995-DeJong #case study
A Case Study of Explanation-Based Control (GD), pp. 167–175.
ICML-1995-DietterichF #learning #perspective
Explanation-Based Learning and Reinforcement Learning: A Unified View (TGD, NSF), pp. 176–184.
ICML-1995-DonohoR #induction #lessons learnt
Lessons from Theory Revision Applied to Constructive Induction (SKD, LAR), pp. 185–193.
ICML-1995-DoughertyKS
Supervised and Unsupervised Discretization of Continuous Features (JD, RK, MS), pp. 194–202.
ICML-1995-Drakopoulos #bound #classification #fault #nearest neighbour
Bounds on the Classification Error of the Nearest Neighbor Rule (JAD), pp. 203–208.
ICML-1995-Duff #problem
Q-Learning for Bandit Problems (MOD), pp. 209–217.
ICML-1995-EngelsonK #reliability
Distilling Reliable Information From Unreliable Theories (SPE, MK), pp. 218–225.
ICML-1995-Fong
A Quantitative Study of Hypothesis Selection (PWLF), pp. 226–234.
ICML-1995-KrishnanLV #learning
Learning to Make Rent-to-Buy Decisions with Systems Applications (PK, PML, JSV), pp. 233–330.
ICML-1995-Fuchs #adaptation #heuristic #learning #parametricity #proving
Learning Proof Heuristics by Adaptive Parameters (MF), pp. 235–243.
ICML-1995-FultonKS #algorithm #multi #performance
Efficient Algorithms for Finding Multi-way Splits for Decision Trees (TF, SK, SS), pp. 244–251.
ICML-1995-GambardellaD #approach #learning #named #problem
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem (LMG, MD), pp. 252–260.
ICML-1995-Gordon #approximate #programming
Stable Function Approximation in Dynamic Programming (GJG), pp. 261–268.
ICML-1995-Greiner #challenge
The Challenge of Revising an Impure Theory (RG), pp. 269–277.
ICML-1995-Hekanaho #concept #learning #multimodal
Symbiosis in Multimodal Concept Learning (JH), pp. 278–285.
ICML-1995-HerbsterW
Tracking the Best Expert (MH, MKW), pp. 286–294.
ICML-1995-KimuraYK #learning #probability
Reinforcement Learning by Stochastic Hill Climbing on Discounted Reward (HK, MY, SK), pp. 295–303.
ICML-1995-KohaviJ #fault #parametricity
Autmatic Parameter Selection by Minimizing Estimated Error (RK, GHJ), pp. 304–312.
ICML-1995-KongD #bias
Error-Correcting Output Coding Corrects Bias and Variance (EBK, TGD), pp. 313–321.
ICML-1995-Lang #learning #named
NewsWeeder: Learning to Filter Netnews (KL), pp. 331–339.
ICML-1995-Lang95a #problem #search-based #synthesis
Hill Climbing Beats Genetic Search on a Boolean Circuit Synthesis Problem of Koza’s (KJL), pp. 340–343.
ICML-1995-LangleyP
Case-Based Acquisition of Place Knowledge (PL, KP), pp. 344–352.
ICML-1995-Littlestone #algorithm #learning
Comparing Several Linear-threshold Learning Algorithms on Tasks Involving Superfluous Attributes (NL), pp. 353–361.
ICML-1995-LittmanCK #learning #policy #scalability
Learning Policies for Partially Observable Environments: Scaling Up (MLL, ARC, LPK), pp. 362–370.
ICML-1995-Lubinsky #classification #consistency #performance #using
Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves (DJL), pp. 371–377.
ICML-1995-MaassW #learning #performance
Efficient Learning with Virtual Threshold Gates (WM, MKW), pp. 378–386.
ICML-1995-McCallum #learning
Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State (AM), pp. 387–395.
ICML-1995-MoriartyM #evolution #learning #performance
Efficient Learning from Delayed Rewards through Symbiotic Evolution (DEM, RM), pp. 396–404.
ICML-1995-Niyogi #complexity #learning
Free to Choose: Investigating the Sample Complexity of Active Learning of Real Valued Functions (PN), pp. 405–412.
ICML-1995-NockG #learning #on the
On Learning Decision Committees (RN, OG), pp. 413–420.
ICML-1995-OliveiraS #graph #order
Inferring Reduced Ordered Decision Graphs of Minimum Description Length (ALO, ALSV), pp. 421–429.
ICML-1995-OliverH #on the
On Pruning and Averaging Decision Trees (JJO, DJH), pp. 430–437.
ICML-1995-Peng #performance #programming
Efficient Memory-Based Dynamic Programming (JP), pp. 438–446.
ICML-1995-PerezR #multi #using
Using Multidimensional Projection to Find Relations (EP, LAR), pp. 447–455.
ICML-1995-Pfahringer
Compression-Based Discretization of Continuous Attributes (BP), pp. 456–463.
ICML-1995-Quinlan
MDL and Categorial Theories (Continued) (JRQ), pp. 464–470.
ICML-1995-RaoGS #question
For Every Generalization Action, Is There Really an Equal and Opposite Reaction? (RBR, DFG, WMS), pp. 471–479.
ICML-1995-SalganicoffU #learning #multi #using
Active Exploration and Learning in real-Valued Spaces using Multi-Armed Bandit Allocation Indices (MS, LHU), pp. 480–487.
ICML-1995-Schmidhuber #complexity
Discovering Solutions with Low Kolmogorov Complexity and High Generalization Capability (JS), pp. 488–496.
ICML-1995-SinghP #algorithm #classification #comparison #induction
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers (MS, GMP), pp. 497–505.
ICML-1995-SmythGF #classification #estimation #kernel #using
Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (PS, AGG, UMF), pp. 506–514.
ICML-1995-SquiresS #automation #machine learning #recognition
Automatic Speaker Recognition: An Application of Machine Learning (BS, CS), pp. 515–521.
ICML-1995-StreetMW #approach #induction #learning #predict
An Inductive Learning Approach to Prognostic Prediction (WNS, OLM, WHW), pp. 522–530.
ICML-1995-Sutton #modelling
TD Models: Modeling the World at a Mixture of Time Scales (RSS), pp. 531–539.
ICML-1995-TowellVGJ #information retrieval #learning
Learning Collection FUsion Strategies for Information Retrieval (GGT, EMV, NKG, BJL), pp. 540–548.
ICML-1995-Wang #approach #incremental #learning
Learning by Observation and Practice: An Incremental Approach for Planning Operator Acquisition (XW), pp. 549–557.
ICML-1995-Weiss #learning
Learning with Rare Cases and Small Disjuncts (GMW), pp. 558–565.
ICML-1995-Wolpert
Horizonal Generalization (DW), pp. 566–574.
ICML-1995-YamazakiPM #ambiguity #learning #natural language
Learning Hierarchies from Ambiguous Natural Language Data (TY, MJP, CJM), pp. 575–583.
ICML-1995-Croft #information retrieval #machine learning
Machine Learning and Information Retrieval (WBC), p. 587.
ICML-1995-Heckerman #learning #network
Learning With Bayesian Networks (DH), p. 588.
ICML-1995-Pomerleau #learning
Learning for Automotive Collision Avoidance and Autonomous Control (DP), p. 589.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.