Assaf Zeevi

Orcid: 0000-0003-1075-6664

Affiliations:
  • Columbia University, New York City, NY, USA
  • Technion - Israel Institute of Technology (former)
  • Stanford University, CA, USA (former, PhD 2001)


According to our database1, Assaf Zeevi authored at least 74 papers between 1996 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Dynamic Pricing with Online Reviews.
Manag. Sci., February, 2023

A Doubly Robust Approach to Sparse Reinforcement Learning.
CoRR, 2023

MNL-Prophet: Sequential Assortment Selection under Uncertainty.
CoRR, 2023

Pareto Front Identification with Regret Minimization.
CoRR, 2023

Bayesian Design Principles for Frequentist Sequential Learning.
Proceedings of the International Conference on Machine Learning, 2023

Improved Algorithms for Multi-period Multi-class Packing Problems with Bandit Feedback.
Proceedings of the International Conference on Machine Learning, 2023

Last Switch Dependent Bandits with Monotone Payoff Functions.
Proceedings of the International Conference on Machine Learning, 2023

Complexity Analysis of a Countable-armed Bandit Problem.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

2022
Dynamic Learning in Large Matching Markets.
SIGMETRICS Perform. Evaluation Rev., August, 2022

Optimal Stopping of a Random Sequence with Unknown Distribution.
Math. Oper. Res., 2022

Practical Nonparametric Sampling Strategies for Quantile-Based Ordinal Optimization.
INFORMS J. Comput., 2022

Exact Optimal Fixed Width Confidence Interval Estimation for the Mean.
Proceedings of the Winter Simulation Conference, 2022

Online Allocation and Learning in the Presence of Strategic Agents.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Bandits with Dynamic Arm-acquisition Costs<sup>*</sup>.
Proceedings of the 58th Annual Allerton Conference on Communication, 2022

2021
The Countable-armed Bandit with Vanishing Arms.
CoRR, 2021

Dynamic Pricing and Learning under the Bass Model.
Proceedings of the EC '21: The 22nd ACM Conference on Economics and Computation, 2021

A Closer Look at the Worst-case Behavior of Multi-armed Bandit Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sparsity-Agnostic Lasso Bandit.
Proceedings of the 38th International Conference on Machine Learning, 2021

Learning to Stop with Surprisingly Few Samples.
Proceedings of the Conference on Learning Theory, 2021

2020
Towards Optimal Problem Dependent Generalization Error Bounds in Statistical Learning Theory.
CoRR, 2020

Upper Counterfactual Confidence Bounds: a New Optimism Principle for Contextual Bandits.
CoRR, 2020

Discriminative Learning via Adaptive Questioning.
CoRR, 2020

Towards Problem-dependent Optimal Learning Rates.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

From Finite to Countable-Armed Bandits.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
MNL-Bandit: A Dynamic Learning Approach to Assortment Selection.
Oper. Res., 2019

2018
Optimal Price and Delay Differentiation in Large-Scale Queueing Systems.
Manag. Sci., 2018

Tractable Sampling Strategies for Ordinal Optimization.
Oper. Res., 2018

On Incomplete Learning and Certainty-Equivalence Control.
Oper. Res., 2018

A General Approach to Multi-Armed Bandits Under Risk Criteria.
Proceedings of the Conference On Learning Theory, 2018

2017
Chasing Demand: Learning and Earning in a Changing Environment.
Math. Oper. Res., 2017

Thompson Sampling for the MNL-Bandit.
Proceedings of the 30th Conference on Learning Theory, 2017

2016
On the tightness of an LP relaxation for rational optimization and its applications.
Oper. Res. Lett., 2016

Optimization in Online Content Recommendation Services: Beyond Click-Through Rates.
Manuf. Serv. Oper. Manag., 2016

Tractable sampling strategies for quantile-based ordinal optimization.
Proceedings of the Winter Simulation Conference, 2016

A Near-Optimal Exploration-Exploitation Approach for Assortment Selection.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

2015
On the (Surprising) Sufficiency of Linear Models for Dynamic Pricing with Demand Learning.
Manag. Sci., 2015

Non-Stationary Stochastic Optimization.
Oper. Res., 2015

Online Time Series Prediction with Missing Data.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Multidimensional stochastic approximation: Adaptive algorithms and applications.
ACM Trans. Model. Comput. Simul., 2014

Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-Myopic Policies.
Oper. Res., 2014

Optimal Exploration-Exploitation in a Multi-Armed-Bandit Problem with Non-stationary Rewards.
CoRR, 2014

Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
Optimal Dynamic Assortment Planning with Demand Learning.
Manuf. Serv. Oper. Manag., 2013

2012
Bayesian Dynamic Pricing Policies: Learning and Earning Under a Binary Prior Distribution.
Manag. Sci., 2012

Blind Network Revenue Management.
Oper. Res., 2012

2011
A Note on Performance Limitations in Bandit Problems With Side Information.
IEEE Trans. Inf. Theory, 2011

General Bounds and Finite-Time Improvement for the Kiefer-Wolfowitz Stochastic Approximation Algorithm.
Oper. Res., 2011

On the Minimax Complexity of Pricing in a Changing Environment.
Oper. Res., 2011

2010
Revenue maximization through "smart" inventory management in reservation-based online advertising.
SIGMETRICS Perform. Evaluation Rev., 2010

Testing the Validity of a Demand Model: An Operations Perspective.
Manuf. Serv. Oper. Manag., 2010

Capacity Sizing Under Parameter Uncertainty: Safety Staffing Principles Revisited.
Manag. Sci., 2010

Time-of-Use pricing policies for offering Cloud Computing as a service.
Proceedings of 2010 IEEE International Conference on Service Operations and Logistics, 2010

Nonparametric Bandits with Covariates.
Proceedings of the COLT 2010, 2010

Revenue maximization in reservation-based online advertising through dynamic inventory management.
Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009
Pointwise Stationary Fluid Models for Stochastic Processing Networks.
Manuf. Serv. Oper. Manag., 2009

Dynamic Pricing Without Knowing the Demand Function: Risk Bounds and Near-Optimal Algorithms.
Oper. Res., 2009

On a Data-Driven Method for Staffing Large Call Centers.
Oper. Res., 2009

An Adaptive Multidimensional Version of the Kiefer-Wolfowitz Stochastic Approximation Algorithm.
Proceedings of the 2009 Winter Simulation Conference, 2009

2008
Portfolio Credit Risk with Extremal Dependence: Asymptotic Analysis and Efficient Simulation.
Oper. Res., 2008

2007
On the inefficiency of state-independent importance sampling in the presence of heavy tails.
Oper. Res. Lett., 2007

Implications of heavy tails on simulation-based ordinal optimization.
Proceedings of the Winter Simulation Conference, 2007

2006
Design and Control of a Large Call Center: Asymptotic Analysis of an LP-Based Method.
Oper. Res., 2006

2005
Dynamic Routing and Admission Control in High-Volume Service Systems: Asymptotic Analysis via Multi-Scale Fluid Limits.
Queueing Syst. Theory Appl., 2005

A Method for Staffing Large Call Centers Based on Stochastic Fluid Models.
Manuf. Serv. Oper. Manag., 2005

Pricing and Design of Differentiated Services: Approximate Analysis and Structural Insights.
Oper. Res., 2005

Expected shortfall in credit portfolios with extremal dependence.
Proceedings of the 37th Winter Simulation Conference, Orlando, FL, USA, December 4-7, 2005, 2005

Importance sampling simulation in the presence of heavy tails.
Proceedings of the 37th Winter Simulation Conference, Orlando, FL, USA, December 4-7, 2005, 2005

2004
Diffusion Approximations for a Multiclass Markovian Service System with "Guaranteed" and "Best-Effort" Service Levels.
Math. Oper. Res., 2004

Dynamic Scheduling of a Multiclass Queue in the Halfin-Whitt Heavy Traffic Regime.
Oper. Res., 2004

2003
Pricing and Capacity Sizing for Systems with Shared Resources: Approximate Solutions and Scaling Relations.
Manag. Sci., 2003

1998
Error Bounds for Functional Approximation and Estimation Using Mixtures of Experts.
IEEE Trans. Inf. Theory, 1998

On the Performance of Vector Quantizers Empirically Designed from Dependent Sources.
Proceedings of the Data Compression Conference, 1998

1997
Density Estimation Through Convex Combinations of Densities: Approximation and Estimation Bounds.
Neural Networks, 1997

1996
Time Series Prediction using Mixtures of Experts.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996


  Loading...