Andreas Krause

According to our database1, Andreas Krause authored at least 231 papers between 2003 and 2018.

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Bibliography

2018
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamic Systems.
CoRR, 2018

Discrete Sampling using Semigradient-based Product Mixtures.
CoRR, 2018

Unsupervised Imitation Learning.
CoRR, 2018

Teaching Multiple Concepts to Forgetful Learners.
CoRR, 2018

Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference.
CoRR, 2018

Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations.
CoRR, 2018

Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs.
CoRR, 2018

Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning.
CoRR, 2018

Differentiable Submodular Maximization.
CoRR, 2018

Submodularity on Hypergraphs: From Sets to Sequences.
CoRR, 2018

Online Variance Reduction for Stochastic Optimization.
CoRR, 2018

Fake News Detection in Social Networks via Crowd Signals.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Scalable k -Means Clustering via Lightweight Coresets.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Differentiable Submodular Maximization.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Online Variance Reduction for Stochastic Optimization.
Proceedings of the Conference On Learning Theory, 2018

Submodularity on Hypergraphs: From Sets to Sequences.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Incentive-Compatible Forecasting Competitions.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Learning to Interact With Learning Agents.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Learning User Preferences to Incentivize Exploration in the Sharing Economy.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Training Gaussian Mixture Models at Scale via Coresets.
Journal of Machine Learning Research, 2017

Machine Learning and Formal Method (Dagstuhl Seminar 17351).
Dagstuhl Reports, 2017

Detecting Fake News in Social Networks via Crowdsourcing.
CoRR, 2017

Learning User Preferences to Incentivize Exploration in the Sharing Economy.
CoRR, 2017

Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints.
CoRR, 2017

Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms.
CoRR, 2017

Stochastic Submodular Maximization: The Case of Coverage Functions.
CoRR, 2017

Learning Implicit Generative Models Using Differentiable Graph Tests.
CoRR, 2017

Learning to Use Learners' Advice.
CoRR, 2017

Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly.
CoRR, 2017

Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization.
CoRR, 2017

Coordinated Online Learning With Applications to Learning User Preferences.
CoRR, 2017

An Online Learning Approach to Generative Adversarial Networks.
CoRR, 2017

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting.
CoRR, 2017

Guarantees for Greedy Maximization of Non-submodular Functions with Applications.
CoRR, 2017

Safe Model-based Reinforcement Learning with Stability Guarantees.
CoRR, 2017

Uniform Deviation Bounds for Unbounded Loss Functions like k-Means.
CoRR, 2017

Scalable and Distributed Clustering via Lightweight Coresets.
CoRR, 2017

Improving Optimization-Based Approximate Inference by Clamping Variables.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Stochastic Submodular Maximization: The Case of Coverage Functions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Differentiable Learning of Submodular Functions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Safe Model-based Reinforcement Learning with Stability Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Interactive Submodular Bandit.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Probabilistic Submodular Maximization in Sub-Linear Time.
Proceedings of the 34th International Conference on Machine Learning, 2017

Differentially Private Submodular Maximization: Data Summarization in Disguise.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten".
Proceedings of the 34th International Conference on Machine Learning, 2017

Guarantees for Greedy Maximization of Non-submodular Functions with Applications.
Proceedings of the 34th International Conference on Machine Learning, 2017

Uniform Deviation Bounds for k-Means Clustering.
Proceedings of the 34th International Conference on Machine Learning, 2017

Distributed and Provably Good Seedings for k-Means in Constant Rounds.
Proceedings of the 34th International Conference on Machine Learning, 2017

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Proper Proxy Scoring Rules.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

Selecting Sequences of Items via Submodular Maximization.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem.
Journal of Machine Learning Research, 2016

Distributed Submodular Maximization.
Journal of Machine Learning Research, 2016

Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions.
CoRR, 2016

Learning Sparse Additive Models with Interactions in High Dimensions.
CoRR, 2016

Safe Exploration in Finite Markov Decision Processes with Gaussian Processes.
CoRR, 2016

Actively Learning Hemimetrics with Applications to Eliciting User Preferences.
CoRR, 2016

Better safe than sorry: Risky function exploitation through safe optimization.
CoRR, 2016

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning.
CoRR, 2016

Horizontally Scalable Submodular Maximization.
CoRR, 2016

Linear-time Outlier Detection via Sensitivity.
CoRR, 2016

Near-optimal Bayesian Active Learning with Correlated and Noisy Tests.
CoRR, 2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation.
CoRR, 2016

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains.
CoRR, 2016

Safe Learning of Regions of Attraction for Uncertain, Nonlinear Systems with Gaussian Processes.
CoRR, 2016

Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics.
CoRR, 2016

Learning programs from noisy data.
Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2016

Safe Exploration in Finite Markov Decision Processes with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variational Inference in Mixed Probabilistic Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Cooperative Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fast and Provably Good Seedings for k-Means.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Linear-Time Outlier Detection via Sensitivity.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Safe controller optimization for quadrotors with Gaussian processes.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Actively Learning Hemimetrics with Applications to Eliciting User Preferences.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Horizontally Scalable Submodular Maximization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Evaluating Task-Dependent Taxonomies for Navigation.
Proceedings of the Fourth AAAI Conference on Human Computation and Crowdsourcing, 2016

Learning and Feature Selection under Budget Constraints in Crowdsourcing.
Proceedings of the Fourth AAAI Conference on Human Computation and Crowdsourcing, 2016

Bayesian optimization for maximum power point tracking in photovoltaic power plants.
Proceedings of the 2016 European Control Conference, 2016

Suggesting Sounds for Images from Video Collections.
Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016

Better safe than sorry: Risky function exploitation through safe optimization.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

Safe learning of regions of attraction for uncertain, nonlinear systems with Gaussian processes.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Learning Sparse Additive Models with Interactions in High Dimensions.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Approximate K-Means++ in Sublinear Time.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Robot navigation in dense human crowds: Statistical models and experimental studies of human-robot cooperation.
I. J. Robotics Res., 2015

Discovering Valuable Items from Massive Data.
CoRR, 2015

Building Hierarchies of Concepts via Crowdsourcing.
CoRR, 2015

Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization.
CoRR, 2015

Information Gathering in Networks via Active Exploration.
CoRR, 2015

Learning to Hire Teams.
CoRR, 2015

Crowd Access Path Optimization: Diversity Matters.
CoRR, 2015

Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures.
CoRR, 2015

Scalable Variational Inference in Log-supermodular Models.
CoRR, 2015

Safe Controller Optimization for Quadrotors with Gaussian Processes.
CoRR, 2015

Predicting Program Properties from "Big Code".
Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 2015

Distributed Submodular Cover: Succinctly Summarizing Massive Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Sampling from Probabilistic Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Discovering Valuable items from Massive Data.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Building Hierarchies of Concepts via Crowdsourcing.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Information Gathering in Networks via Active Exploration.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Non-Monotone Adaptive Submodular Maximization.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Safe Exploration for Optimization with Gaussian Processes.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Scalable Variational Inference in Log-supermodular Models.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Coresets for Nonparametric Estimation - the Case of DP-Means.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Higher-Order Inference for Multi-class Log-Supermodular Models.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Learning to Hire Teams.
Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

Crowd Access Path Optimization: Diversity Matters.
Proceedings of the Third AAAI Conference on Human Computation and Crowdsourcing, 2015

Sequential Information Maximization: When is Greedy Near-optimal?
Proceedings of The 28th Conference on Learning Theory, 2015

Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Incentivizing Users for Balancing Bike Sharing Systems.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Lazier Than Lazy Greedy.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Submodular Surrogates for Value of Information.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization.
Journal of Machine Learning Research, 2014

Near-Optimally Teaching the Crowd to Classify.
CoRR, 2014

Distributed Submodular Maximization.
CoRR, 2014

Lazier Than Lazy Greedy.
CoRR, 2014

A Utility-Theoretic Approach to Privacy in Online Services.
CoRR, 2014

Optimal Value of Information in Graphical Models.
CoRR, 2014

Near Optimal Bayesian Active Learning for Decision Making.
CoRR, 2014

Online Submodular Maximization under a Matroid Constraint with Application to Learning Assignments.
CoRR, 2014

Efficient Informative Sensing using Multiple Robots.
CoRR, 2014

Community sense and response systems: your phone as quake detector.
Commun. ACM, 2014

Sequential Decision Making in Computational Sustainability via Adaptive Submodularity.
AI Magazine, 2014

Explore-exploit in top-N recommender systems via Gaussian processes.
Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

Community sense-and-response systems: Your phone as seismometer.
Proceedings of the 2014 IEEE International Conference on Pervasive Computing and Communication Workshops, 2014

Efficient Partial Monitoring with Prior Information.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Efficient Sampling for Learning Sparse Additive Models in High Dimensions.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

From MAP to Marginals: Variational Inference in Bayesian Submodular Models.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Streaming submodular maximization: massive data summarization on the fly.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Fully autonomous focused exploration for robotic environmental monitoring.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Near-Optimally Teaching the Crowd to Classify.
Proceedings of the 31th International Conference on Machine Learning, 2014

Active Detection via Adaptive Submodularity.
Proceedings of the 31th International Conference on Machine Learning, 2014

Contextual Procurement in Online Crowdsourcing Markets.
Proceedings of the Seconf AAAI Conference on Human Computation and Crowdsourcing, 2014

Near Optimal Bayesian Active Learning for Decision Making.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Submodular Function Maximization.
Proceedings of the Tractability: Practical Approaches to Hard Problems, 2014

2013
Optimizing waypoints for monitoring spatiotemporal phenomena.
I. J. Robotics Res., 2013

Towards a living earth simulator
CoRR, 2013

Incentives for Privacy Tradeoff in Community Sensing.
CoRR, 2013

Truthful incentives in crowdsourcing tasks using regret minimization mechanisms.
Proceedings of the 22nd International World Wide Web Conference, 2013

Distributed Submodular Maximization: Identifying Representative Elements in Massive Data.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

High-Dimensional Gaussian Process Bandits.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Robust landmark selection for mobile robot navigation.
Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2013

A fresh perspective: learning to sparsify for detection in massive noisy sensor networks.
Proceedings of the 12th International Conference on Information Processing in Sensor Networks (co-located with CPS Week 2013), 2013

Active Learning for Level Set Estimation.
Proceedings of the IJCAI 2013, 2013

Robot navigation in dense human crowds: the case for cooperation.
Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

Active Learning for Multi-Objective Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization.
Proceedings of the 30th International Conference on Machine Learning, 2013

Incentives for Privacy Tradeoff in Community Sensing.
Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing, 2013

Submodularity in Machine Learning and Vision.
Proceedings of the British Machine Vision Conference, 2013

2012
Inferring Networks of Diffusion and Influence.
TKDD, 2012

Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting.
IEEE Trans. Information Theory, 2012

Learning Fourier Sparse Set Functions.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Near-optimal Nonmyopic Value of Information in Graphical Models
CoRR, 2012

"Smart" design space sampling to predict Pareto-optimal solutions.
Proceedings of the SIGPLAN/SIGBED Conference on Languages, 2012

Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization.
Proceedings of the 29th International Conference on Machine Learning, 2012

Joint Optimization and Variable Selection of High-dimensional Gaussian Processes.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Robust sensor placements at informative and communication-efficient locations.
TOSN, 2011

Submodularity and its applications in optimized information gathering.
ACM TIST, 2011

Simultaneous Optimization of Sensor Placements and Balanced Schedules.
IEEE Trans. Automat. Contr., 2011

Greedy Dictionary Selection for Sparse Representation.
J. Sel. Topics Signal Processing, 2011

Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization.
J. Artif. Intell. Res., 2011

Adaptive Submodular Optimization under Matroid Constraints
CoRR, 2011

Contextual Gaussian Process Bandit Optimization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Crowdclustering.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Scalable Training of Mixture Models via Coresets.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Demo abstract, the next big one: Detecting earthquakes and other rare events from community-based sensors.
Proceedings of the 10th International Conference on Information Processing in Sensor Networks, 2011

The next big one: Detecting earthquakes and other rare events from community-based sensors.
Proceedings of the 10th International Conference on Information Processing in Sensor Networks, 2011

Randomized Sensing in Adversarial Environments.
Proceedings of the IJCAI 2011, 2011

Dynamic Resource Allocation in Conservation Planning.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
SFO: A Toolbox for Submodular Function Optimization.
Journal of Machine Learning Research, 2010

A Utility-Theoretic Approach to Privacy in Online Services.
J. Artif. Intell. Res., 2010

Efficient Minimization of Decomposable Submodular Functions
CoRR, 2010

Near-Optimal Bayesian Active Learning with Noisy Observations
CoRR, 2010

Inferring Networks of Diffusion and Influence
CoRR, 2010

Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
CoRR, 2010

Online Distributed Sensor Selection
CoRR, 2010

Efficient Minimization of Decomposable Submodular Functions.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Discriminative Clustering by Regularized Information Maximization.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Near-Optimal Bayesian Active Learning with Noisy Observations.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Inferring networks of diffusion and influence.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Unfreezing the robot: Navigation in dense, interacting crowds.
Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010

Online distributed sensor selection.
Proceedings of the 9th International Conference on Information Processing in Sensor Networks, 2010

Informative path planning for an autonomous underwater vehicle.
Proceedings of the IEEE International Conference on Robotics and Automation, 2010

Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Submodular Dictionary Selection for Sparse Representation.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Budgeted Nonparametric Learning from Data Streams.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization.
Proceedings of the COLT 2010, 2010

2009
Efficient Informative Sensing using Multiple Robots.
J. Artif. Intell. Res., 2009

Optimal Value of Information in Graphical Models.
J. Artif. Intell. Res., 2009

Gaussian Process Bandits without Regret: An Experimental Design Approach
CoRR, 2009

Online Learning of Assignments that Maximize Submodular Functions
CoRR, 2009

Optimizing Sensing: From Water to the Web.
IEEE Computer, 2009

Online Learning of Assignments.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Simultaneous placement and scheduling of sensors.
Proceedings of the 8th International Conference on Information Processing in Sensor Networks, 2009

Nonmyopic Adaptive Informative Path Planning for Multiple Robots.
Proceedings of the IJCAI 2009, 2009

2008
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies.
Journal of Machine Learning Research, 2008

Toward Community Sensing.
Proceedings of the 7th International Conference on Information Processing in Sensor Networks, 2008

A Utility-Theoretic Approach to Privacy and Personalization.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
Robust, low-cost, non-intrusive sensing and recognition of seated postures.
Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology, 2007

Selecting Observations against Adversarial Objectives.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Cost-effective outbreak detection in networks.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Efficient Planning of Informative Paths for Multiple Robots.
Proceedings of the IJCAI 2007, 2007

Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach.
Proceedings of the Machine Learning, 2007

Nonmyopic Informative Path Planning in Spatio-Temporal Models.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

Near-optimal Observation Selection using Submodular Functions.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Context-Aware Mobile Computing: Learning Context-Dependent Personal Preferences from a Wearable Sensor Array.
IEEE Trans. Mob. Comput., 2006

Near-optimal sensor placements: maximizing information while minimizing communication cost.
Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, 2006

Data association for topic intensity tracking.
Proceedings of the Machine Learning, 2006

2005
Near-optimal Nonmyopic Value of Information in Graphical Models.
Proceedings of the UAI '05, 2005

Intelligent light control using sensor networks.
Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, 2005

Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing.
Proceedings of the Ninth IEEE International Symposium on Wearable Computers (ISWC 2005), 2005

Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Near-optimal sensor placements in Gaussian processes.
Proceedings of the Machine Learning, 2005

2004
Mobile decision support for transplantation patient data.
I. J. Medical Informatics, 2004

Development and implementation of a parallel algorithm for the fast design of oligonucleotide probe sets for diagnostic DNA microarrays.
Concurrency - Practice and Experience, 2004

2003
PDA-based decision support and documentation for transplantation surgery data.
Proceedings of the Mobiles Computing in der Medizin, 2003

Mobile wireless acess to EHR and PACS in clinical practice.
Proceedings of the Mobiles Computing in der Medizin, 2003

SenSay: A Context-Aware Mobile Phone.
Proceedings of the 7th International Symposium on Wearable Computers (ISWC 2003), 2003

Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing.
Proceedings of the 7th International Symposium on Wearable Computers (ISWC 2003), 2003

Accurate Method for Fast Design of Diagnostic Oligonucleotide Probe Sets for DNA Microarrays.
Proceedings of the 17th International Parallel and Distributed Processing Symposium (IPDPS 2003), 2003


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