## Lorenza Saitta

*Proceedings of the 13th International Conference on Machine Learning*

ICML, 1996.

@proceedings{ICML-1996, address = "Bari, Italy", editor = "Lorenza Saitta", isbn = "1-55860-419-7", publisher = "{Morgan Kaufmann}", title = "{Proceedings of the 13th International Conference on Machine Learning}", year = 1996, }

### Contents (66 items)

- ICML-1996-AbeL #learning #modelling #using #word
- Learning Word Association Norms Using Tree Cut Pair Models (NA, HL), pp. 3–11.
- ICML-1996-AkkusG #classification #nearest neighbour
- K Nearest Neighbor Classification on Feature Projections (AA, HAG), pp. 12–19.
- ICML-1996-BanderaVBHB #visual notation
- Residual Q-Learning Applied to Visual Attention (CB, FJV, JMB, MEH, LCBI), pp. 20–27.
- ICML-1996-Baum #towards
- Toward a Model of Mind as a Laissez-Faire Economy of Idiots (EBB), pp. 28–36.
- ICML-1996-BlanzieriK #learning #network #online
- Learning Radial Basis Function Networks On-line (EB, PK), pp. 37–45.
- ICML-1996-Bostrom #induction #logic programming #regular expression #source code
- Theory-Guideed Induction of Logic Programs by Inference of Regular Languages (HB), pp. 46–53.
- ICML-1996-BoutilierD #approximate #programming
- Approximate Value Trees in Structured Dynamic Programming (CB, RD), pp. 54–62.
- ICML-1996-BoyanM #evaluation #learning #scalability
- Learning Evaluation Functions for Large Acyclic Domains (JAB, AWM), pp. 63–70.
- ICML-1996-Burges
- Simplified Support Vector Decision Rules (CJCB), pp. 71–77.
- ICML-1996-CarbonaraS #knowledge base #performance #refinement
- Improving the Efficiency of Knowledge Base Refinement (LC, DHS), pp. 78–86.
- ICML-1996-Caruana #algorithm #learning #multi
- Algorithms and Applications for Multitask Learning (RC), pp. 87–95.
- ICML-1996-DietterichKM #framework #learning
- Applying the Waek Learning Framework to Understand and Improve C4.5 (TGD, MJK, YM), pp. 96–104.
- ICML-1996-DomingosP #classification #independence
- Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier (PMD, MJP), pp. 105–112.
- ICML-1996-DonohoR #induction #using
- Constructive Induction Using Fragmentary Knowledge (SKD, LAR), pp. 113–121.
- ICML-1996-EmdeW #learning #relational
- Relational Instance-Based Learning (WE, DW), pp. 122–130.
- ICML-1996-EngelsonK #identification
- Identifying the Information Contained in a Flawed Theory (SPE, MK), pp. 131–138.
- ICML-1996-EzawaSN #learning #network #risk management
- Learning Goal Oriented Bayesian Networks for Telecommunications Risk Management (KJE, MS, SWN), pp. 139–147.
- ICML-1996-FreundS #algorithm
- Experiments with a New Boosting Algorithm (YF, RES), pp. 148–156.
- ICML-1996-FriedmanG #learning #network
- Discretizing Continuous Attributes While Learning Bayesian Networks (NF, MG), pp. 157–165.
- ICML-1996-GeibelW #concept #learning #relational
- Learning Relational Concepts with Decision Trees (PG, FW), pp. 166–174.
- ICML-1996-GoetzKM #adaptation #learning #online
- On-Line Adaptation of a Signal Predistorter through Dual Reinforcement Learning (PG, SK, RM), pp. 175–181.
- ICML-1996-GoldingR
- Applying Winnow to Context-Sensitive Spelling Correction (ARG, DR), pp. 182–190.
- ICML-1996-GoldmanS #algorithm #empirical
- A Theoretical and Empirical Study of a Noise-Tolerant Algorithm to Learn Geormetric Patterns (SAG, SDS), pp. 191–199.
- ICML-1996-GordonS #learning #parametricity #statistics
- Nonparametric Statistical Methods for Experimental Evaluations of Speedup Learning (GJG, AMS), pp. 200–206.
- ICML-1996-GreinerGR #classification #learning
- Learning Active Classifiers (RG, AJG, DR), pp. 207–215.
- ICML-1996-GreinerGK
- Exploiting the Omission of Irrelevant Data (RG, AJG, AK), pp. 216–224.
- ICML-1996-GrolimundG #memory management #nearest neighbour
- Speeding-up Nearest Neighbour Memories: The Template Tree Case Memory Organisation (SG, JGG), pp. 225–233.
- ICML-1996-Hekanaho #concept #learning
- Background Knowledge in GA-based Concept Learning (JH), pp. 234–242.
- ICML-1996-HelmboldSSW #multi #online #using
- On-Line Portfolio Selection Using Multiplicative Updates (DPH, RES, YS, MKW), pp. 243–251.
- ICML-1996-IttnerS
- Non-Linear Decision Trees — NDT (AI, MS), pp. 252–257.
- ICML-1996-JappyNG #horn clause #learning #robust #source code
- Negative Robust Learning Results from Horn Clause Programs (PJ, RN, OG), pp. 258–265.
- ICML-1996-KoenigS #distance #learning #navigation
- Passive Distance Learning for Robot Navigation (SK, RGS), pp. 266–274.
- ICML-1996-KahaviW #bias #composition
- Bias Plus Variance Decomposition for Zero-One Loss Functions (RK, DW), pp. 275–283.
- ICML-1996-KollerS #feature model #towards
- Toward Optimal Feature Selection (DK, MS), pp. 284–292.
- ICML-1996-Kubat
- Second Tier for Decision Trees (MK), pp. 293–301.
- ICML-1996-Lathrop #on the
- On the Learnability of the Uncomputable (RHL), pp. 302–309.
- ICML-1996-LittmanS #convergence
- A Generalized Reinforcement-Learning Model: Convergence and Applications (MLL, CS), pp. 310–318.
- ICML-1996-LiuS #approach #feature model #probability
- A Probabilistic Approach to Feature Selection — A Filter Solution (HL, RS), pp. 319–327.
- ICML-1996-Mahadevan #learning
- Sensitive Discount Optimality: Unifying Discounted and Average Reward Reinforcement Learning (SM), pp. 328–336.
- ICML-1996-Munos #algorithm #convergence #learning
- A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning (RM), pp. 337–345.
- ICML-1996-OatesC #multi
- Searching for Structure in Multiple Streams of Data (TO, PRC), pp. 346–354.
- ICML-1996-OkamotoY #analysis #classification #nearest neighbour
- Theoretical Analysis of the Nearest Neighbor Classifier in Noisy Domains (SO, NY), pp. 355–363.
- ICML-1996-OliverBW #learning #using
- Unsupervised Learning Using MML (JJO, RAB, CSW), pp. 364–372.
- ICML-1996-PendrithR #difference #learning
- Actual Return Reinforcement Learning versus Temporal Differences: Some Theoretical and Experimental Results (MDP, MRKR), pp. 373–381.
- ICML-1996-Perez #learning #representation
- Representing and Learning Quality-Improving Search Control Knowledge (MAP), pp. 382–390.
- ICML-1996-PerezR #concept #learning
- Learning Despite Concept Variation by Finding Structure in Attribute-based Data (EP, LAR), pp. 391–399.
- ICML-1996-RaviseS #evolution #fault
- An Advanced Evolution Should Not Repeat its Past Errors (CR, MS), pp. 400–408.
- ICML-1996-ReddyTR #composition #empirical #learning
- Theory-guided Empirical Speedup Learning of Goal Decomposition Rules (CR, PT, SR), pp. 409–417.
- ICML-1996-Roverso #abstraction #knowledge base #multi #scalability
- Analogy Access by Mapping Spreading and Abstraction in Large, Multifunctional Knowledge Bases (DR), pp. 418–426.
- ICML-1996-Saerens #fault #learning
- Non Mean Square Error Criteria for the Training of Learning Machines (MS), pp. 427–434.
- ICML-1996-SahamiHS #categorisation #model-to-text #multi
- Applying the Multiple Cause Mixture Model to Text Categorization (MS, MAH, ES), pp. 435–443.
- ICML-1996-Sebag #approach #bias
- Delaying the Choice of Bias: A Disjunctive Version Space Approach (MS), pp. 444–452.
- ICML-1996-SinghP #classification #learning #network #performance
- Efficient Learning of Selective Bayesian Network Classifiers (MS, GMP), pp. 453–461.
- ICML-1996-Suzuki #algorithm #learning #network #performance #using
- Learning Bayesian Belief Networks Based on the Minimum Description Length Principle: An Efficient Algorithm Using the B & B Technique (JS), pp. 462–470.
- ICML-1996-TadepalliO #approximate #domain model #learning #modelling #scalability
- Scaling Up Average Reward Reinforcement Learning by Approximating the Domain Models and the Value Function (PT, DO), pp. 471–479.
- ICML-1996-TaeC #information management
- Experimental Knowledge Acquisition for Planning (KST, DJC), pp. 480–488.
- ICML-1996-ThrunO #algorithm #learning #multi
- Discovering Structure in Multiple Learning Tasks: The TC Algorithm (ST, JO), pp. 489–497.
- ICML-1996-Ting #predict
- The Characterisation of Predictive Accuracy and Decision Combination (KMT), pp. 498–506.
- ICML-1996-TirriKM #learning
- Prababilistic Instance-Based Learning (HT, PK, PM), pp. 507–515.
- ICML-1996-WallaceKD
- Causal Discovery via MML (CSW, KBK, HD), pp. 516–524.
- ICML-1996-Widmer #incremental #recognition
- Recognition and Exploitation of Contextual CLues via Incremental Meta-Learning (GW), pp. 525–533.
- ICML-1996-WieringS
- Solving POMDPs with Levin Search and EIRA (MW, JS), pp. 534–542.
- ICML-1996-ZuckerG #learning #performance #representation
- Representation Changes for Efficient Learning in Structural Domains (JDZ, JGG), pp. 543–551.
- ICML-1996-Mannila #data mining #machine learning #mining
- Data Mining and Machine Learning (HM), p. 555.
- ICML-1996-Moore #learning
- Reinforcement Learning in Factories: The Auton Project (AWM0), p. 556.
- ICML-1996-Vapnik #statistics
- Statistical Theory of Generalization (VV), p. 557.

30 ×#learning

6 ×#algorithm

6 ×#multi

5 ×#classification

5 ×#network

5 ×#using

4 ×#performance

3 ×#concept

3 ×#nearest neighbour

3 ×#online

6 ×#algorithm

6 ×#multi

5 ×#classification

5 ×#network

5 ×#using

4 ×#performance

3 ×#concept

3 ×#nearest neighbour

3 ×#online