Thomas G. Dietterich | Academic Influence

Thomas G. Dietterich's AcademicInfluence.com Rankings

Thomas G. Dietterich

Computer Science

#1203

World Rank

#1243

Historical Rank

#626

USA Rank

Machine Learning

#52

World Rank

#52

Historical Rank

#20

USA Rank

Database

#119

World Rank

#122

Historical Rank

#67

USA Rank

Artificial Intelligence

#125

World Rank

#128

Historical Rank

#57

USA Rank

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Computer Science

Thomas G. Dietterich's Degrees

PhD Computer Science Stanford University
Masters Computer Science Stanford University

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Why Is Thomas G. Dietterich Influential?

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According to Wikipedia, Thomas G. Dietterich is emeritus professor of computer science at Oregon State University. He is one of the pioneers of the field of machine learning. He served as executive editor of Machine Learning and helped co-found the Journal of Machine Learning Research. In response to the media's attention on the dangers of artificial intelligence, Dietterich has been quoted for an academic perspective to a broad range of media outlets including National Public Radio, Business Insider, Microsoft Research, CNET, and The Wall Street Journal.

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Thomas G. Dietterich's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Machine learning (1996) (16769)
Ensemble Methods in Machine Learning (2000) (6684)
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms (1998) (3351)
Solving Multiclass Learning Problems via Error-Correcting Output Codes (1994) (2979)
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization (2000) (2732)
Solving the Multiple Instance Problem with Axis-Parallel Rectangles (1997) (2608)
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations (2018) (1821)
Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition (1999) (1554)
Machine-Learning Research Four Current Directions (1997) (1017)
Adaptive computation and machine learning (1998) (901)
Deep Anomaly Detection with Outlier Exposure (2018) (867)
Learning with Many Irrelevant Features (1991) (788)
Machine-Learning Research (1997) (733)
Machine Learning for Sequential Data: A Review (2002) (714)
The eBird enterprise: An integrated approach to development and application of citizen science (2014) (635)
Pruning Adaptive Boosting (1997) (614)
Learning Boolean Concepts in the Presence of Many Irrelevant Features (1994) (599)
Overfitting and undercomputing in machine learning (1995) (510)
Error-Correcting Output Coding Corrects Bias and Variance (1995) (457)
A Reinforcement Learning Approach to job-shop Scheduling (1995) (443)
In Advances in Neural Information Processing Systems 15 (1991) (387)
Readings in Machine Learning (1991) (382)
A model of the mechanical design process based on empirical data (1988) (375)
The MAXQ Method for Hierarchical Reinforcement Learning (1998) (355)
A Comparative Review of Selected Methods for Learning from Examples (1983) (338)
A Unifying Review of Deep and Shallow Anomaly Detection (2020) (338)
Improving SVM accuracy by training on auxiliary data sources (2004) (312)
TaskTracer: a desktop environment to support multi-tasking knowledge workers (2005) (280)
Editors. Advances in Neural Information Processing Systems (2002) (265)
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods (2004) (264)
Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs (1991) (259)
Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods (1981) (216)
Improving the Performance of Radial Basis Function Networks by Learning Center Locations (1991) (203)
Interacting meaningfully with machine learning systems: Three experiments (2009) (197)
Machine Learning Bias, Statistical Bias, and Statistical Variance of Decision Tree Algorithms (2008) (176)
An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms (1995) (168)
Toward harnessing user feedback for machine learning (2007) (161)
Systematic construction of anomaly detection benchmarks from real data (2013) (160)
Training conditional random fields via gradient tree boosting (2004) (159)
A Conditional Multinomial Mixture Model for Superset Label Learning (2012) (148)
A study of distance-based machine learning algorithms (1994) (148)
Learning and Inductive Inference (1982) (145)
Principal Curvature-Based Region Detector for Object Recognition (2007) (141)
Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects (2007) (141)
Cyber SA: Situational Awareness for Cyber Defense (2010) (138)
Efficient Algorithms for Identifying Relevant Features (1992) (135)
Detecting insider threats in a real corporate database of computer usage activity (2013) (135)
Structured machine learning: the next ten years (2008) (134)
High-Performance Job-Shop Scheduling With A Time-Delay TD(λ) Network (1995) (129)
Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations (2018) (128)
Bioinformatics The Machine Learning Approach 2nd ed. (2001) (126)
An Overview of MAXQ Hierarchical Reinforcement Learning (2000) (121)
Discovering Patterns in Sequences of Events (1985) (119)
Map Misclassification Can Cause Large Errors in Landscape Pattern Indices: Examples from Habitat Fragmentation (2006) (118)
A hybrid learning system for recognizing user tasks from desktop activities and email messages (2006) (117)
Applying the Waek Learning Framework to Understand and Improve C4.5 (1996) (115)
A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping (1990) (114)
Learning from Sparse Data by Exploiting Monotonicity Constraints (2005) (112)
Steps Toward Robust Artificial Intelligence (2017) (110)
Incorporating Expert Feedback into Active Anomaly Discovery (2016) (108)
Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers (2000) (98)
Automatic discovery and transfer of MAXQ hierarchies (2008) (95)
Learning to Predict Sequences (1985) (94)
Compass: A shape-based machine learning tool for drug design (1994) (93)
Learning first-order probabilistic models with combining rules (2005) (93)
Learning Probabilistic Behavior Models in Real-Time Strategy Games (2011) (87)
Pruning Improves Heuristic Search for Cost-Sensitive Learning (2002) (87)
State Abstraction in MAXQ Hierarchical Reinforcement Learning (1999) (85)
Learning non-redundant codebooks for classifying complex objects (2009) (83)
Reinforcement Learning Via Practice and Critique Advice (2010) (82)
Low Bias Bagged Support Vector Machines (2003) (81)
Transfer Learning with an Ensemble of Background Tasks (2005) (80)
Spatiotemporal Models for Data-Anomaly Detection in Dynamic Environmental Monitoring Campaigns (2011) (79)
Allowing a wildfire to burn: estimating the effect on future fire suppression costs (2013) (79)
Selecting Appropriate Representations for Learning from Examples (1986) (74)
Batch Value Function Approximation via Support Vectors (2001) (71)
Learnability of the Superset Label Learning Problem (2014) (71)
Dictionary-free categorization of very similar objects via stacked evidence trees (2009) (71)
Explanation-Based Learning and Reinforcement Learning: A Unified View (1995) (71)
A Meta-Analysis of the Anomaly Detection Problem (2015) (66)
The life and times of files and information: a study of desktop provenance (2010) (65)
A Study of Explanation-Based Methods for Inductive Learning (1989) (62)
Algorithms for Identifying Relevant Features (1992) (61)
Locally Adaptive Nearest Neighbor Algorithms (1993) (61)
Open Category Detection with PAC Guarantees (2018) (61)
Predicting User Tasks : I Know What You ’ re Doing ! (2005) (60)
Automated processing and identification of benthic invertebrate samples (2010) (60)
Collective Graphical Models (2011) (58)
Active Imitation Learning via Reduction to I.I.D. Active Learning (2012) (57)
Learning at the knowledge level (2004) (56)
Improved Class Probability Estimates from Decision Tree Models (2003) (54)
Feedback-Guided Anomaly Discovery via Online Optimization (2018) (53)
Limitations on Inductive Learning (1989) (52)
Machine learning for cognitive networks : technology assessment and research challenges (2003) (51)
Rise of concerns about AI (2015) (50)
Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter (2015) (49)
An experimental comparison of the nearest-neighbor and nearest-hyperrectangle algorithms (1995) (48)
Incorporating Boosted Regression Trees into Ecological Latent Variable Models (2011) (47)
Fewer clicks and less frustration: reducing the cost of reaching the right folder (2006) (45)
A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction (1993) (44)
Next-generation phenomics for the Tree of Life (2013) (43)
Machine Learning in Ecosystem Informatics and Sustainability (2009) (43)
Methods for cost-sensitive learning (2002) (43)
A Comparison of ID3 and Backpropagation for English Text-To-Speech Mapping (2004) (42)
Detecting and correcting user activity switches: algorithms and interfaces (2009) (41)
Approximate Inference in Collective Graphical Models (2013) (40)
Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification (2010) (40)
Discovering frequent work procedures from resource connections (2009) (40)
State Aggregation in Monte Carlo Tree Search (2014) (39)
Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods (1979) (38)
Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams (2007) (37)
High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network (1995) (37)
Sequential Feature Explanations for Anomaly Detection (2015) (37)
Prune-and-Score: Learning for Greedy Coreference Resolution (2014) (36)
A data representation for collaborative mechanical design (1992) (36)
Incorporating Feedback into Tree-based Anomaly Detection (2017) (35)
Real-Time Detection of Task Switches of Desktop Users (2007) (35)
Guiding Scientific Discovery with Explanations Using DEMUD (2013) (34)
Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar (2013) (34)
Bias-Variance Analysis and Ensembles of SVM (2002) (33)
Gradient Tree Boosting for Training Conditional Random Fields (2008) (32)
Learning Scripts as Hidden Markov Models (2014) (32)
Learning at the Knowledge Level (1986) (31)
Applying General Induction Methods to the Card Game Eleusis (1980) (31)
Knowledge Compilation: A Symposium (1991) (30)
ℋC-search for structured prediction in computer vision (2015) (29)
Efficient Value Function Approximation Using Regression Trees (1999) (28)
Achieving High-Accuracy Text-to-Speech with Machine Learning (1997) (28)
Converting English text to speech: a machine learning approach (1991) (28)
Stacked spatial-pyramid kernel: An object-class recognition method to combine scores from random trees (2011) (27)
Penalized likelihood methods improve parameter estimates in occupancy models (2015) (26)
Learning decision trees for loss minimization in multi-class problems (1999) (26)
Multiple Classifier Systems (2000) (25)
Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games (2012) (25)
Mining IC test data to optimize VLSI testing (2000) (24)
The Handbook of Brain Theory and Neural Networks (2002) (23)
Active lmitation learning: formal and practical reductions to I.I.D. learning (2014) (23)
Segmentation of touching insects based on optical flow and NCuts (2013) (23)
Model-based Policy Gradient Reinforcement Learning (2003) (22)
Advances in neural information processing systems : proceedings of the ... conference (1989) (22)
PAC optimal MDP planning with application to invasive species management (2015) (22)
Robust artificial intelligence and robust human organizations (2018) (22)
A Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions (2006) (22)
Learning and Reasoning (2003) (21)
Statistical Machine Learning for Large-Scale Optimization (2000) (21)
Hierarchical Explanation-Based Reinforcement Learning (1997) (21)
The Divide-and-Conquer Manifesto (2000) (20)
An aquatic insect imaging system to automate insect classification (2008) (20)
The Role of the Critic in Learning Systems (1984) (20)
PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs (2013) (19)
Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning (2018) (19)
Anomaly detection in the presence of missing values for weather data quality control (2018) (19)
Why Error Correcting Output Coding Works (1994) (19)
Inverting Grice's Maxims to Learn Rules from Natural Language Extractions (2011) (18)
A POMDP Approximation Algorithm That Anticipates the Need to Observe (2000) (18)
Editorial Exploratory research in machine learning (1990) (18)
Spatial interactions and optimal forest management on a fire-threatened landscape (2017) (17)
The TaskTracer system (2005) (16)
α-min: A Compact Approximate Solver For Finite-Horizon POMDPs (2015) (16)
Constraint propagation techniques for theory-driven data interpretation (artificial intelligence, machine learning) (1985) (16)
Reconstructing Velocities of Migrating Birds from Weather Radar - A Case Study in Computational Sustainability (2014) (16)
Reinforcement Matching Using Region Context (2006) (15)
A Study of Explanation-Based Methods for (1989) (15)
Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning (2011) (14)
FORLOG : A Logic-based Architecture for Design (1987) (14)
An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration (2012) (14)
Pattern Recognition for Ecological Science and Environmental Monitoring: An Initial Report (2006) (14)
Facilitating testing and debugging of Markov Decision Processes with interactive visualization (2015) (14)
Confidence Calibration for Domain Generalization under Covariate Shift (2021) (14)
Integrating Learning from Examples into the Search for Diagnostic Policies (2005) (13)
An Ensemble Learning and Problem Solving Architecture for Airspace Management (2009) (13)
Learning to Detect Basal Tubules of Nematocysts in SEM Images (2013) (13)
Transductive Optimization of Top k Precision (2015) (12)
Machine Learning Methods for High Level Cyber Situation Awareness (2010) (12)
Learning Greedy Policies for the Easy-First Framework (2015) (12)
What Good Are Experiments? (1989) (11)
The Test Incorporation Theory of Problem Solving (1986) (11)
Proceedings of the 14th International Conference on Neural Information Processing Systems: Natural and Synthetic (2001) (11)
Machine Learning 1 (1996) (10)
A comparison of ID3 and backpropagation for English text-to-speech mapping (2004) (10)
Finite Sample Complexity of Rare Pattern Anomaly Detection (2016) (10)
Memory-Based Methods for Regression and Classification (1993) (10)
SRL2004 ICML 2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (2004) (10)
Three New Algorithms to Solve N-POMDPs (2017) (10)
The use of provenance in information retrieval (2007) (10)
The Familiarity Hypothesis: Explaining the Behavior of Deep Open Set Methods (2022) (9)
Integrating Multiple Learning Components through Markov Logic (2008) (9)
Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA (2001) (9)
Machine learning for computational sustainability (2012) (9)
The Test Incorporation Hypothesis and the Weak Methods (1986) (9)
Learning cost-sensitive diagnostic policies from data (2003) (9)
Gaussian Approximation of Collective Graphical Models (2014) (9)
Data mining for manufacturing control: an application in optimizing IC tests (2003) (9)
Interactive visualization for testing Markov Decision Processes: MDPVIS (2017) (9)
Forward Chaining Logic Programming with the ATMS (1987) (9)
Progressive Abstraction Refinement for Sparse Sampling (2015) (8)
A Wrapper Method for Cost-Sensitive Learning via Stratification (2007) (8)
Learning About Systems That Contain State Variables (1984) (8)
Anomaly Detection Meta-Analysis Benchmarks (2016) (8)
A Multi-agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation (2002) (7)
A Divide and Conquer Approach to Learning from Prior Knowledge (2000) (7)
FolderPredictor: Reducing the cost of reaching the right folder (2011) (7)
Abstraction, Reformulation, and Approximation (2000) (7)
Optimal Spatial-Dynamic Management of Stochastic Species Invasions (2018) (7)
Learning visual dictionaries and decision lists for object recognition (2008) (7)
The Role of Restoration and Key Ecological Invasion Mechanisms in Optimal Spatial-Dynamic Management of Invasive Species (2018) (7)
Towards learning rules from natural texts (2010) (7)
A Knowledge Base Data Representation for Collaborative Mechanical Design (1991) (7)
Sample-Based Tree Search with Fixed and Adaptive State Abstractions (2017) (7)
Gaussian process regression with mismatched models (2002) (7)
Action Refinement in Reinforcement Learning by Probability Smoothing (2002) (7)
Discovering Anomalies by Incorporating Feedback from an Expert (2020) (6)
Learning MDP Action Models Via Discrete Mixture Trees (2008) (6)
Two Algorithms for Transfer Learning (6)
Evaluating Online Text Classification Algorithms for Email Prediction in TaskTracer (2009) (6)
Active EM to reduce noise in activity recognition (2007) (6)
Exploiting monotonicity via logistic regression in Bayesian network learning (2013) (6)
Managing Fragmented Fire-Threatened Landscapes with Spatial Externalities (2020) (6)
Crowds Replicate Performance of Scientific Experts Scoring Phylogenetic Matrices of Phenotypes (2018) (6)
Solving K-MDPs (2020) (6)
Exploiting functional vocabularies to learn structural descriptions (1986) (6)
Performance Comparison between Human Engineered & Machine Learned Letter-to-sound Rules for English: a Machine Learning Success Story (1993) (6)
Efficient Exploration for Constrained MDPs (2018) (5)
Support Vectors for Reinforcement Learning (2001) (5)
Factoring Exogenous State for Model-Free Monte Carlo (2017) (5)
Learning Rules from Incomplete Examples via Implicit Mention Models (2011) (5)
Knowledge Compilation: Bridging the Gap between Specification and Implementation (1991) (5)
Knowledge Compilation to Speed Up Numerical Optimization (1991) (5)
On Learning More Concepts (1992) (5)
Two heuristics for solving POMDPs having a delayed need to observe (2004) (5)
Fundamental Experimental Research in Machine Learning (1997) (5)
Fast Simulation for Computational Sustainability Sequential Decision Making Problems (2016) (5)
Constructing High-Accuracy Letter-to-Phoneme Rules with Machine Learning (2001) (5)
Inductive Learning from Preclassified Training Examples (1990) (5)
Learning at the Knowledge Level Dietterich%oregon-state@csnet-relay (1986) (5)
Varieties of Operationality (5)
05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis (2006) (4)
Conformal Prediction Intervals for Markov Decision Process Trajectories (2022) (4)
Value Function Approximations and Job-Shop Scheduling (1995) (4)
Limitations on Inductive Learning (extended Abstract) (1997) (4)
Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada] (2001) (4)
Calibrating recurrent sliding window classifiers for sequential supervised learning (2003) (4)
An Efficient ATMS for Equivalence Relations (1988) (4)
The Search for Equilibrium in Markov Games (2007) (3)
Machine Learning in Engineering Automation (1991) (3)
Applying machine learning for prediction, recommendation, and integration (2009) (3)
A Summary of Machine Learning Papers From IJCAI-85 (3)
Machine Learning in Ecosystem Informatics (2007) (3)
Machine Learning and Ecosystem Informatics: Challenges and Opportunities (2009) (3)
Pruning Adaptive Boosting *** Icml-97 Final Draft *** (2015) (3)
Three-quarter Sibling Regression for Denoising Observational Data (2019) (3)
Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007 (2008) (3)
Knowledge Compilation to Speed Up Numerical Optimisation (1991) (2)
The EG project: recent progress (1986) (2)
Who speaks for AI? (2016) (2)
Oracle Analysis of Representations for Deep Open Set Detection (2022) (2)
The MAXQMethod for Hierarchical Reinforcement Learning (2012) (2)
BENCHMARKING NEURAL NETWORK ROBUSTNESS (2018) (2)
Improving Intelligent Assistants for Desktop Activities (2007) (2)
User Initiated Learning for Adaptive Interfaces (2009) (2)
Emergence of Motion-sensitive Neurons Properties by Learning Sparse Code for Natural Moving Images (2001) (2)
Is Fine Grained Classification Different ? (2013) (2)
Learning Rules from Incomplete Examples via Observation Models (2011) (2)
Fast Optimization of Wildfire Suppression Policies with SMAC (2017) (2)
Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA) (2021) (2)
Design of an Automated System for Imaging and Sorting Soil Mesofauna (2011) (2)
Stabilizing Value Function Approximation with the BFBP Algorithm (2001) (2)
Learning From Demonstrations via Structured Prediction (2007) (1)
Conditional mixture models for precipitation data quality control (2020) (1)
A family of large margin linear classifiers and its application in dynamic environments (2009) (1)
Machine Learning for the Knowledge Plane (2006) (1)
Deep Convolution for Irregularly Sampled Temporal Point Clouds (2021) (1)
Improving Automated Email Tagging with Implicit Feedback (2015) (1)
05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis (2005) (1)
Proceedings of the 13th International Conference on Neural Information Processing Systems (2000) (1)
Image features and learning algorithms for biological, generic and social object recognition (2009) (1)
Editorial: New Editorial Board Members (1994) (1)
Evaluating wildland fire liability standards – does regulation incentivise good management? (2020) (1)
State Abstraction in Maxq Hierarchical Reinforcement Learning Category: Reinforcement Learning and Control Preference: Oral (2000) (1)
Purposive Behavior Acqui- Sition for a Real Robot by Vision-based Reinforcement Learning. a Mulit- Agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-based (1)
Reinforcement learning in scheduling (1994) (1)
Proposed metrics for transfer learning (2006) (1)
Can We Achieve Open Category Detection with Guarantees? (2018) (1)
Just enough die-level test: optimizing ic test via machine learning and decision theory (1998) (1)
MDPVIS: An Interactive Visualization for Testing Markov Decision Processes (2015) (1)
Theory and Praxis of Machine Learning (2008) (1)
Robust artificial intelligence and robust human organizations (2018) (1)
Editorial (2004) (1)
Learning Rules from Incomplete Examples via a Probabilistic Mention Model (2011) (1)
DARPA's Role in Machine Learning (2020) (1)
07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis (2007) (1)
News and notes (1988) (0)
Institutional Knowledge at Singapore Management University Research Collection School Of Information Systems School of Information Systems 2013 Approximate Inference in Collective Graphical Models (2014) (0)
AAAI-07 Workshop Reports (2007) (0)
Probabilistic models for quality control in environmental sensor networks (2012) (0)
2 The Knowledge Level 2 . 1 Newell ’ s description of the knowledge level (1986) (0)
News and notes (1986) (0)
Human Computation (2018) (0)
News and notes (1989) (0)
News and notes (1987) (0)
The TaskTracker System (2005) (0)
Solving Simulator-Defined MDPs for Natural Resource Management (2013) (0)
Hidden Heterogeneity: When to Choose Similarity-Based Calibration (2022) (0)
News and notes (1991) (0)
News and Notes (1984) (0)
KI-LEARN: Knowledge-Intensive Learning Methods for Knowledge-Rich/Data-Poor Domains (2006) (0)
1 Design Histories as an Aid to Redesign in Mechanical Engineering — (0)
Multiple-Model Induction in (2009) (0)
News and notes (1994) (0)
Recovery from Interruptions: Knowledge Workers' Strategies, Failures and Envisioned Solutions (2005) (0)
Learning Optimal Search Control for Engineering Optimization (1992) (0)
News and notes (1986) (0)
Category Detection with PAC Guarantees (2018) (0)
Statistical Machine Learning for Large-Scale Optimization Contributors (0)
AN ABSTRACT OF THE DISSERTATION OF Guohua Hao for the degree of Doctor of Philosophy in Computer Science presented on July 21, 2009. Title: Efficient Training and Feature Induction in Sequential Supervised Learning Abstract approved: (2009) (0)
AN ABSTRACT OF THE THESIS OF Michael Lam for the degree of Master of Science in Computer Science presented on May 15, 2014. Title: Object Detection in Biological Images Using a Search-Based Framework Abstract approved: (2014) (0)
News and notes (1993) (0)
Editorial (2004) (0)
Learning Rules from Incomplete Examples: A Pragmatic Approach (2010) (0)
Hybrid Computational Models for Skill Acquisition (1998) (0)
FolderPredictor (2011) (0)
Stabilizing Value Function with the (2001) (0)
Theory and Practice of Machine Learning (Dagstuhl Seminar 9702) (2021) (0)
AN ABSTRACT OF THE THESIS OF Shriprakash Sinha for the degree of Master of Science in Computer Science (2009) (0)
AN ABSTRACT OF THE THESIS OF Shriprakash Sinha for the degree of Master of Science in Computer Science (2009) (0)
Symbolic Methods in Numerical Optimization (1991) (0)
Ao Revisited (2012) (0)
News and notes (1987) (0)
Calibrating Recurrent Sliding Window (2012) (0)
News and Notes (1987) (0)
Reinforcement Learning with Exogenous States and Rewards (2023) (0)
News and Notes (2005) (0)
ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation (2022) (0)
Zero-Shot Learning and Detection of Teeth in Images of Bat Skulls (2013) (0)
Toward Visualization Methods for Interactive Improvement of MDP Specifications (2014) (0)
News and Notes (1987) (0)
News and notes (1993) (0)
Deep Reading and Learning (2017) (0)
News and Notes (1986) (0)
Machine Learning for Real-Time Decision Making (2001) (0)
Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005 (2006) (0)
Editorial (1996) (0)
Computing Research for the Climate Crisis (2021) (0)
News and Notes (1987) (0)
A Study of Maximal-coverage Learning Algorithms (2007) (0)
News and Notes (1971) (0)
Will My Robot Achieve My Goals? Predicting the Probability that an MDP Policy Reaches a User-Specified Behavior Target (2022) (0)
Sequential Feature Explanations for Anomaly Detection Md (2015) (0)
News and Notes (2005) (0)
Title: Activity Recognition in Desktop Environments (2009) (0)
Theory and Praxis of Machine Learning (Dagstuhl Seminar 9426) (2021) (0)
PAC Guarantees and Effective Algorithms for Detecting Novel Categories (2022) (0)
Bayesian time series classification (2002) (0)
News and notes (1987) (0)
News and notes (1978) (0)
A Unified Approach to Abductive Inference (2014) (0)
Model based approximation methods for reinforcement learning (2006) (0)
Induction: Weak but essential (1986) (0)

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