Jacob D. Abernethy

According to our database1, Jacob D. Abernethy
  • authored at least 64 papers between 2006 and 2017.
  • has a "Dijkstra number"2 of four.

Timeline

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Bibliography

2017
Online Learning via Differential Privacy.
CoRR, 2017

Addendum to "A Market Framework for Eliciting Private Data".
CoRR, 2017

How to Train Your DRAGAN.
CoRR, 2017

A Data Science Approach to Understanding Residential Water Contamination in Flint.
CoRR, 2017

On Frank-Wolfe and Equilibrium Computation.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A Data Science Approach to Understanding Residential Water Contamination in Flint.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016
Flint Water Crisis: Data-Driven Risk Assessment Via Residential Water Testing.
CoRR, 2016

Data Science in Service of Performing Arts: Applying Machine Learning to Predicting Audience Preferences.
CoRR, 2016

Analysing RateMyProfessors Evaluations Across Institutions, Disciplines, and Cultures: The Tell-Tale Signs of a Good Professor.
Proceedings of the Social Informatics - 8th International Conference, 2016

Rate of Price Discovery in Iterative Combinatorial Auctions.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

Threshold Bandits, With and Without Censored Feedback.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Utilizing high-dimensional features for real-time robotic applications: Reducing the curse of dimensionality for recursive Bayesian estimation.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Fighting Bandits with a New Kind of Smoothness.
CoRR, 2015

Rate of Price Discovery in Iterative Combinatorial Auctions.
CoRR, 2015

Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier.
CoRR, 2015

Actively Purchasing Data for Learning.
CoRR, 2015

Low-Cost Learning via Active Data Procurement.
Proceedings of the Sixteenth ACM Conference on Economics and Computation, 2015

A Market Framework for Eliciting Private Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Fighting Bandits with a New Kind of Smoothness.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Financialized methods for market-based multi-sensor fusion.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

2014
On risk measures, market making, and exponential families.
SIGecom Exchanges, 2014

Online Linear Optimization via Smoothing.
CoRR, 2014

Information Aggregation in Exponential Family Markets.
CoRR, 2014

Jamming defense against a resource-replenishing adversary in multi-channel wireless systems.
Proceedings of the 12th International Symposium on Modeling and Optimization in Mobile, 2014

Information aggregation in exponential family markets.
Proceedings of the ACM Conference on Economics and Computation, 2014

A general volume-parameterized market making framework.
Proceedings of the ACM Conference on Economics and Computation, 2014

Online Linear Optimization via Smoothing.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Efficient Market Making via Convex Optimization, and a Connection to Online Learning.
ACM Trans. Economics and Comput., 2013

Minimax Optimal Algorithms for Unconstrained Linear Optimization.
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

Adaptive Market Making via Online Learning.
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

How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal.
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

Large-Scale Bandit Problems and KWIK Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Interior-Point Methods for Full-Information and Bandit Online Learning.
IEEE Trans. Information Theory, 2012

A Characterization of Scoring Rules for Linear Properties.
Proceedings of the COLT 2012, 2012

Minimax Option Pricing Meets Black-Scholes in the Limit
CoRR, 2012

Minimax option pricing meets black-scholes in the limit.
Proceedings of the 44th Symposium on Theory of Computing Conference, 2012

2011
Does an Efficient Calibrated Forecasting Strategy Exist?
Proceedings of the COLT 2011, 2011

Blackwell Approachability and No-Regret Learning are Equivalent.
Proceedings of the COLT 2011, 2011

A Collaborative Mechanism for Crowdsourcing Prediction Problems
CoRR, 2011

An optimization-based framework for automated market-making.
Proceedings of the Proceedings 12th ACM Conference on Electronic Commerce (EC-2011), 2011

A Collaborative Mechanism for Crowdsourcing Prediction Problems.
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

2010
Graph regularization methods for Web spam detection.
Machine Learning, 2010

An Optimization-Based Framework for Automated Market-Making
CoRR, 2010

Blackwell Approachability and Low-Regret Learning are Equivalent
CoRR, 2010

Repeated Games against Budgeted Adversaries.
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

Can We Learn to Gamble Efficiently?
Proceedings of the COLT 2010, 2010

A Regularization Approach to Metrical Task Systems.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization.
Journal of Machine Learning Research, 2009

A Stochastic View of Optimal Regret through Minimax Duality
CoRR, 2009

Minimax Games with Bandits.
Proceedings of the COLT 2009, 2009

An Efficient Bandit Algorithm for sqrt(T) Regret in Online Multiclass Prediction?.
Proceedings of the COLT 2009, 2009

Beating the Adaptive Bandit with High Probability.
Proceedings of the COLT 2009, 2009

A Stochastic View of Optimal Regret through Minimax Duality.
Proceedings of the COLT 2009, 2009

2008
Eliciting Consumer Preferences Using Robust Adaptive Choice Questionnaires.
IEEE Trans. Knowl. Data Eng., 2008

A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
CoRR, 2008

When Random Play is Optimal Against an Adversary.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Optimal Stragies and Minimax Lower Bounds for Online Convex Games.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Web spam identification through content and hyperlinks.
Proceedings of the AIRWeb 2008, 2008

2007
Online discovery of similarity mappings.
Proceedings of the Machine Learning, 2007

Multitask Learning with Expert Advice.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

2006
Low-rank matrix factorization with attributes
CoRR, 2006

Continuous Experts and the Binning Algorithm.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006


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