K. Seppi

发表

Task similarity measures for transfer in reinforcement learning task libraries

J.L. Carroll, K. Seppi, J. Carroll, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Reinforcement Learning Task Clustering ( RLTC )

Todd S. Peterson, J. Carroll, K. Seppi, 2003 .

Women in CS: Changing the Women or Changing the World?

K. Seppi, Naomi Johnson, J. Garcia, 2019, 2019 IEEE Frontiers in Education Conference (FIE).

A Bayesian CMAC for High Assurance Learning

J. Carroll, K. Seppi, 2007 .

Super-resolution via recapture and Bayesian effect modeling

K. Seppi, B. Morse, D. Ventura, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

Publications 2005-0101 Prioritization Methods for Accelerating MDP Solvers

K. Seppi, 2018 .

No free lunch, bayesian inference, and utility: a decision-theoretic approach to optimization

Christopher K. Monson, K. Seppi, Kevin Seppi, 2006 .

Human-Centered and Interactive: Expanding the Impact of Topic Models

Jordan L. Boyd-Graber, N. Elmqvist, K. Seppi, 2016 .

No-Free-Lunch and Bayesian Optimality

James L. Carroll, Kevin D. Seppi, J. Carroll, 2007 .

2 The Unified Bayesian Decision Theoretic Model ( UBDTM )

J. Carroll, K. Seppi, 2007 .

Publications 2004-0101 Guided Model Checking with a Bayesian Metaheuristic

K. Seppi, Michael D. Jones, Peter Lamborn, 2018 .

Input-to-State Stability Analysis on Particle Swarm Optimization Daqing

K. Seppi, M. Goodrich, Daqing Yi, 2015 .

Cache Performance of Priority Metrics for MDP Solvers

D. Wingate, K. Seppi, 2022 .

Tutorial 7—Adaptive Business Intelligence - Evolutionary Computation for Real World

Qingfu Zhang, Zbigniew Michalewicz, Riccardo Poli, 2007 .

Cooperation-based Clustering for Profit-maximizing Organizational Design

Sean C. Warnick, Kevin D. Seppi, Christophe G. Giraud-Carrier, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

2 The Role of Cost and Benefit

Eric K. Ringger, J. Carroll, K. Seppi, 2008 .

Trajectories and Influencing Factors of Student Confidence Across a Semester

K. Seppi, R. Moulder, Naomi Johnson, 2019, 2019 IEEE Frontiers in Education Conference (FIE).

Evaluating machine-assisted annotation in under-resourced settings

Eric K. Ringger, Deryle W. Lonsdale, K. Seppi, 2013, Language Resources and Evaluation.

Prioritization Methods for Accelerating MDP Solvers

Kevin D. Seppi, David Wingate, D. Wingate, 2005, J. Mach. Learn. Res..

P3VI: a partitioned, prioritized, parallel value iterator

Kevin D. Seppi, David Wingate, D. Wingate, 2004, ICML.

A Utile Function Optimizer

James L. Carroll, Kevin D. Seppi, Christopher K. Monson, 2007, 2007 IEEE Congress on Evolutionary Computation.

Particle Swarm Optimization in Dynamic Pricing

Sean C. Warnick, Kevin D. Seppi, Christopher K. Monson, 2006, 2006 IEEE International Conference on Evolutionary Computation.

A Graphical Model for Evolutionary Optimization

Kevin D. Seppi, Christopher K. Monson, K. Seppi, 2008, Evolutionary Computation.

Digging into user control: perceptions of adherence and instability in transparent models

Kevin Seppi, Leah Findlater, Alison Smith, 2020, IUI.

Closing the Loop: User-Centered Design and Evaluation of a Human-in-the-Loop Topic Modeling System

Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater, 2018, IUI.

The human touch: How non-expert users perceive, interpret, and fix topic models

Niklas Elmqvist, Jordan L. Boyd-Graber, Kevin D. Seppi, 2017, Int. J. Hum. Comput. Stud..

An Analytic and Empirical Evaluation of Return-on-Investment-Based Active Learning

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2015, LAW@NAACL-HLT.

Parallel Active Learning: Eliminating Wait Time with Minimal Staleness

Eric K. Ringger, Paul Felt, Robbie Haertel, 2010, HLT-NAACL 2010.

Assessing the Costs of Sampling Methods in Active Learning for Annotation

Eric K. Ringger, James L. Carroll, Kevin D. Seppi, 2008, ACL.

Assessing the Costs of Machine-Assisted Corpus Annotation through a User Study

Eric K. Ringger, James L. Carroll, Kevin D. Seppi, 2008, LREC.

Active Learning for Part-of-Speech Tagging: Accelerating Corpus Annotation

Eric K. Ringger, James L. Carroll, Kevin D. Seppi, 2007, LAW@ACL.

The rJokes Dataset: a Large Scale Humor Collection

Kevin D. Seppi, Orion Weller, K. Seppi, 2020, LREC.

Humor Detection: A Transformer Gets the Last Laugh

Kevin Seppi, Orion Weller, K. Seppi, 2019, EMNLP.

A bayesian decision theoretical approach to supervised learning, selective sampling, and empirical function optimization

James L. Carroll, Kevin D. Seppi, J. Carroll, 2010 .

You Don’t Have Time to Read This: An Exploration of Document Reading Time Prediction

Quinn Snell, Kevin D. Seppi, Jordan Hildebrandt, 2020, ACL.

Topics Over Nonparametric Time: A Supervised Topic Model Using Bayesian Nonparametric Density Estimation

Eric K. Ringger, Kevin D. Seppi, Daniel David Walker, 2012, BMA.

Preprocessor Selection for Machine Learning Pipelines pdf

Kevin D. Seppi, Christophe G. Giraud-Carrier, Brandon Schoenfeld, 2018, ArXiv.

Automatic Evaluation of Local Topic Quality pdf

Jordan L. Boyd-Graber, Kevin D. Seppi, Jeffrey Lund, 2019, ACL.

Semantic Annotation Aggregation with Conditional Crowdsourcing Models and Word Embeddings

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2016, COLING.

Using Transfer Learning to Assist Exploratory Corpus Annotation

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2014, LREC.

First Results in a Study Evaluating Pre-annotation and Correction Propagation for Machine-Assisted Syriac Morphological Analysis

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2012, LREC.

A Probabilistic Morphological Analyzer for Syriac

Eric K. Ringger, Kevin D. Seppi, Robbie Haertel, 2010, Conference on Empirical Methods in Natural Language Processing.

Tag Dictionaries Accelerate Manual Annotation

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2010, LREC.

CCASH: A Web Application Framework for Efficient, Distributed Language Resource Development

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2010, LREC.

Accelerating Corpus Annotation through Active Learning

Eric K. Ringger, James L. Carroll, Kevin D. Seppi, 2008 .

Evaluating machine-assisted annotation in under-resourced settings

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2014, Lang. Resour. Evaluation.

Evaluating Lemmatization Models for Machine-Assisted Corpus-Dictionary Linkage

Eric K. Ringger, Paul Felt, Kevin Black, 2014, LREC.

Compiling and Annotating a Syriac Corpus

Eric K. Ringger, David Taylor, James L. Carroll, 2008 .

Modeling the Annotation Process for Ancient Corpus Creation

Eric K. Ringger, James L. Carroll, Robbie Haertel, 2007 .

Exposing origin-seeking bias in PSO

Kevin D. Seppi, Christopher K. Monson, K. Seppi, 2005, GECCO '05.

What you Sculpt is What you Get: Modeling Physical Interactive Devices with Clay and 3D Printed Widgets

Michael D. Jones, Dan R. Olsen, Kevin D. Seppi, 2016, CHI.

Turning Bayesian model averaging into Bayesian model combination

Tony R. Martinez, James L. Carroll, Kristine Monteith, 2011, The 2011 International Joint Conference on Neural Networks.

Why Didn’t You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models

Jordan L. Boyd-Graber, Kevin D. Seppi, Leah Findlater, 2019, ACL.

Tandem Anchoring: a Multiword Anchor Approach for Interactive Topic Modeling

Jordan L. Boyd-Graber, Kevin D. Seppi, Jeffrey Lund, 2017, ACL.

Guided model checking with a Bayesian meta-heuristic

Michael D. Jones, Kevin D. Seppi, Peter Lamborn, 2004, Proceedings. Fourth International Conference on Application of Concurrency to System Design, 2004. ACSD 2004..

Super-resolution via recapture and Bayesian effect modeling

Dan Ventura, Bryan S. Morse, Kevin D. Seppi, 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

MRPSO: MapReduce particle swarm optimization

Kevin D. Seppi, Christopher K. Monson, Andrew W. McNabb, 2007, GECCO '07.

Bayesian optimization models for particle swarms

Kevin D. Seppi, Christopher K. Monson, K. Seppi, 2005, GECCO '05.

A speculative approach to parallelization in particle swarm optimization

Kevin D. Seppi, Matthew Gardner, Andrew W. McNabb, 2012, Swarm Intelligence.

Intelligent cooperative control for urban tracking with Unmanned Air Vehicles

Huili Yu, Kevin Cook, Everett Bryan, 2013, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

Homotopy-aware RRT*: Toward human-robot topological path-planning

Michael A. Goodrich, Daqing Yi, Kevin D. Seppi, 2016, 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

Fast Inference for Interactive Models of Text

Eric K. Ringger, Paul Felt, Kevin D. Seppi, 2016, COLING.

Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types

Eric K. Ringger, Jordan L. Boyd-Graber, Paul Felt, 2018, COLING.

A Multi-Site Joint Replication of a Design Patterns Experiment Using Moderator Variables to Generalize across Contexts

Jeffrey C. Carver, Natalia Juristo Juzgado, Sira Vegas, 2016, IEEE Transactions on Software Engineering.

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA

Eric K. Ringger, Jordan L. Boyd-Graber, Paul Felt, 2015, CoNLL.

Early Gains Matter: A Case for Preferring Generative over Discriminative Crowdsourcing Models

Eric K. Ringger, Paul Felt, Kevin Black, 2015, NAACL.

Parallel PSO using MapReduce

Kevin D. Seppi, Christopher K. Monson, Andrew W. McNabb, 2007, 2007 IEEE Congress on Evolutionary Computation.

Studies in the dynamics of economic systems

K. Seppi, S. Warnick, C. Giraud-Carrier, 2005, Proceedings of 2005 IEEE Conference on Control Applications, 2005. CCA 2005..