Yishay Mansour

Q: What Schools Are Affiliated With Yishay Mansour

Yishay Mansour is affiliated with the following schools: Technion – Israel Institute of Technology, Tel Aviv University, Massachusetts Institute of Technology

Yishay Mansour's AcademicInfluence.com Rankings

Yishay Mansour

Computer Science

#3887

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#4084

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Machine Learning

#596

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#603

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computer-science Degrees

Yishay Mansour

Mathematics

#5211

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#7350

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Measure Theory

#637

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#874

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mathematics Degrees

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Computer Science
Mathematics

Yishay Mansour's Degrees

PhD Computer Science Tel Aviv University
Masters Computer Science Tel Aviv University
Bachelors Mathematics Tel Aviv University

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Yishay Mansour'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

Policy Gradient Methods for Reinforcement Learning with Function Approximation (1999) (5252)
Constant depth circuits, Fourier transform, and learnability (1989) (742)
Domain Adaptation: Learning Bounds and Algorithms (2009) (640)
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes (1999) (625)
Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems (2006) (623)
Learning decision trees using the Fourier spectrum (1991) (482)
Domain Adaptation with Multiple Sources (2008) (465)
Learning Rates for Q-learning (2004) (439)
PAC Bounds for Multi-armed Bandit and Markov Decision Processes (2002) (363)
A construction of a cipher from a single pseudorandom permutation (1997) (345)
From External to Internal Regret (2005) (312)
Three Approaches for Personalization with Applications to Federated Learning (2020) (312)
Nash Convergence of Gradient Dynamics in General-Sum Games (2000) (297)
Agnostically learning halfspaces (2005) (294)
On the learnability of discrete distributions (1994) (292)
Learning Bounds for Importance Weighting (2010) (289)
Weakly learning DNF and characterizing statistical query learning using Fourier analysis (1994) (279)
On the boosting ability of top-down decision tree learning algorithms (1996) (255)
Improved second-order bounds for prediction with expert advice (2005) (247)
An Omega(D log (N/D)) Lower Bound for Broadcast in Radio Networks (1998) (229)
Implementing the “Wisdom of the Crowd” (2013) (225)
The Shrinking Generator (1994) (223)
Strong price of anarchy (2007) (221)
An Ω(D log(N/D)) lower bound for broadcast in radio networks (1993) (217)
Buffer overflow management in QoS switches (2001) (214)
The computational complexity of universal hashing (1990) (213)
An Information-Theoretic Analysis of Hard and Soft Assignment Methods for Clustering (1997) (211)
An Experimental and Theoretical Comparison of Model Selection Methods (1995) (209)
Distributed Learning, Communication Complexity and Privacy (2012) (191)
Approximate Planning in Large POMDPs via Reusable Trajectories (1999) (189)
Thompson Sampling for Complex Online Problems (2013) (178)
Online Markov Decision Processes (2009) (167)
Learning Boolean Functions via the Fourier Transform (1994) (161)
Regret Minimization for Reserve Prices in Second-Price Auctions (2013) (161)
Convergence Time to Nash Equilibria (2003) (159)
Time optimal self-stabilizing synchronization (1993) (149)
On nash equilibria for a network creation game (2014) (142)
Multiple Source Adaptation and the Rényi Divergence (2009) (136)
Randomized Interpolation and Approximation of Sparse Polynomials (1992) (136)
Competitive queue policies for differentiated services (2000) (130)
Spill code minimization techniques for optimizing compliers (1989) (127)
Strong equilibrium in cost sharing connection games (2007) (127)
Mechanism design via machine learning (2005) (125)
Convergence time to Nash equilibrium in load balancing (2007) (125)
Algorithmic Game Theory: Learning, Regret Minimization, and Equilibria (2007) (122)
Making the Most of Your Samples (2014) (120)
Broadcast in radio networks (1995) (117)
A Construction of a Cioher From a Single Pseudorandom Permutation (1991) (115)
Applying the Waek Learning Framework to Understand and Improve C4.5 (1996) (115)
Delay and Cooperation in Nonstochastic Bandits (2016) (114)
Online Linear Quadratic Control (2018) (113)
A Fast, Bottom-Up Decision Tree Pruning Algorithm with Near-Optimal Generalization (1998) (112)
Item pricing for revenue maximization (2008) (110)
Centralized broadcast in multihop radio networks (2003) (107)
Learning Linear-Quadratic Regulators Efficiently with only √T Regret (2019) (105)
On Completeness and Soundness in Interactive Proof Systems (1989) (104)
Competitive queueing policies for QoS switches (2003) (103)
Non-price equilibria in markets of discrete goods (2011) (102)
Results on learnability and the Vapnik-Chervonenkis dimension (1988) (101)
Nonstochastic Multi-Armed Bandits with Graph-Structured Feedback (2014) (100)
Bayesian Incentive-Compatible Bandit Exploration (2015) (98)
How long to equilibrium? The communication complexity of uncoupled equilibrium procedures (2010) (98)
On the Complexity of Policy Iteration (1999) (97)
An O(nlog log n) learning algorithm for DNF under the uniform distribution (1992) (95)
Online Convex Optimization in Adversarial Markov Decision Processes (2019) (93)
Jitter control in QoS networks (1998) (93)
Fast convergence of selfish rerouting (2005) (93)
Pessimistic Decision Tree Pruning Based on Tree Size (1997) (91)
Computation in noisy radio networks (2005) (89)
Reducing mechanism design to algorithm design via machine learning (2007) (88)
Efficient on-line call control algorithms (1993) (86)
Generalization bounds for averaged classifiers (2004) (84)
Optimal smoothing schedules for real-time streams (2004) (84)
Experts in a Markov Decision Process (2004) (83)
Improved Competitive Guarantees for QoS Buffering (2003) (81)
Phantom: a simple and effective flow control scheme (1996) (78)
Auctions with Budget Constraints (2004) (77)
Bayesian Exploration: Incentivizing Exploration in Bayesian Games (2016) (76)
From Bandits to Experts: A Tale of Domination and Independence (2013) (75)
On the convergence of regret minimization dynamics in concave games (2009) (74)
Bandwidth allocation with preemption (1995) (74)
Estimating a mixture of two product distributions (1999) (72)
Reliable communication over unreliable channels (1994) (72)
Almost k-wise independence versus k-wise independence (2003) (69)
An O(n^(log log n)) Learning Algorithm for DNT under the Uniform Distribution (1995) (68)
Competitive algorithms for VWAP and limit order trading (2004) (68)
Improved generalization bounds for robust learning (2018) (63)
Interactive proof systems: Provers that never fail and random selection (1987) (63)
Learning with attribute costs (2005) (61)
The impossibility of implementing reliable communication in the face of crashes (1993) (61)
A Local Computation Approximation Scheme to Maximum Matching (2013) (60)
An approximation algorithm for minimum-cost network design (1994) (58)
Converting Online Algorithms to Local Computation Algorithms (2012) (58)
Learning monotone ku DNF formulas on product distributions (1991) (56)
Learning and inference in the presence of corrupted inputs (2015) (56)
Polynomial end-to-end communication (1989) (56)
Boosting Using Branching Programs (2000) (56)
Generalization Bounds for Decision Trees (2000) (55)
On diffusing updates in a Byzantine environment (1999) (55)
Greedy Packet Scheduling on Shortest Paths (1993) (54)
Efficient Nash Computation in Large Population Games with Bounded Influence (2002) (54)
Harmonic buffer management policy for shared memory switches (2002) (54)
Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret (2019) (54)
Improved equilibria via public service advertising (2009) (53)
Bid optimization for broad match ad auctions (2009) (52)
Welfare and Profit Maximization with Production Costs (2011) (52)
Online Learning versus Offline Learning (1995) (51)
On agnostic boosting and parity learning (2008) (50)
Fast Planning in Stochastic Games (2000) (50)
Online trading algorithms and robust option pricing (2006) (49)
Action Elimination and Stopping Conditions for Reinforcement Learning (2003) (48)
Why averaging classifiers can protect against overfitting (2001) (48)
Reinforcement Learning in POMDPs Without Resets (2005) (48)
Convergence of Optimistic and Incremental Q-Learning (2001) (48)
Spill Code Minimization Techniques for Optimizing Compilers (1989) (48)
Learning Multiple Tasks using Shared Hypotheses (2012) (47)
Eecient On-line Call Control Algorithms (1993) (46)
On construction of k-wise independent random variables (1994) (46)
Efficient graph topologies in network routing games (2009) (45)
Selective Call Out and Real Time Bidding (2010) (45)
Adversarially Robust Streaming Algorithms via Differential Privacy (2020) (45)
Loss-bounded analysis for differentiated services (2001) (44)
Doubleclick Ad Exchange Auction (2012) (44)
Efficient algorithms for learning to play repeated games against computationally bounded adversaries (1995) (43)
Approximate Equivalence of Markov Decision Processes (2003) (43)
Near-optimal Regret Bounds for Stochastic Shortest Path (2020) (43)
The communication complexity of uncoupled nash equilibrium procedures (2007) (42)
Competitive buffer management for shared-memory switches (2008) (41)
Diffusion without false rumors: on propagating updates in a Byzantine environment (2003) (41)
Data link layer: two impossibility results (1988) (40)
Upward Max Min Fairness (2012) (40)
Optimizing TCP Retransmission Timeout (2005) (40)
Privately Learning Thresholds: Closing the Exponential Gap (2019) (39)
Item pricing for revenue maximization (2008) (39)
Learning Under Persistent Drift (1997) (38)
Online Stochastic Shortest Path with Bandit Feedback and Unknown Transition Function (2019) (37)
The Price of Uncertainty (2009) (37)
Online Learning for Global Cost Functions (2009) (37)
Dynamic bandwidth allocation policies (1996) (36)
Competitve buffer management for shared-memory switches (2001) (36)
Convergence Complexity of Optimistic Rate-Based Flow-Control Algorithms (1999) (36)
Classification with Low Rank and Missing Data (2015) (35)
Reliable Agnostic Learning (2012) (35)
ERA: A Framework for Economic Resource Allocation for the Cloud (2017) (35)
Robust domain adaptation (2014) (35)
Regret to the best vs. regret to the average (2007) (35)
Lower bounds for integer greatest common divisor computations (1988) (35)
A Time-Optimal Self-Stabilizing Synchronizer Using A Phase Clock (2007) (34)
Competing Bandits: Learning Under Competition (2017) (34)
Optimal smoothing schedules for real-time streams (extended abstract) (2000) (34)
Agnostic Boosting (2001) (34)
Simple learning algorithms for decision trees and multivariate polynomials (1995) (34)
Approximation Schemes for Sequential Posted Pricing in Multi-unit Auctions (2010) (34)
Trade-offs between communication throughput and parallel time (1993) (33)
4 Learning , Regret minimization , and Equilibria (2006) (33)
Circumventing the Price of Anarchy: Leading Dynamics to Good Behavior (2013) (33)
Top-$k$ Combinatorial Bandits with Full-Bandit Feedback (2019) (33)
Exploiting Ontology Structures and Unlabeled Data for Learning (2013) (33)
Slide-The Key to Polynomial End-to-End Communication (1997) (33)
Nonstochastic Bandits with Composite Anonymous Feedback (2018) (32)
Competitive Management of Non-preemptive Queues with Multiple Values (2003) (32)
Position Auctions with Bidder-Specific Minimum Prices (2008) (32)
On Nash Equilibria for a Network Creation Game (2006) (32)
On the Complexity of Learning with Kernels (2014) (31)
epsilon-Discrepancy Sets and Their Application for Interpolation of Sparse Polynomials (1995) (29)
Lower Bounds for Computations with the Floor Operation (1989) (29)
Prediction with Corrupted Expert Advice (2020) (29)
Efficient candidate screening under multiple tests and implications for fairness (2019) (28)
Regret Minimization With Concept Drift (2010) (27)
Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits (2019) (26)
Combining Multiple Heuristics (2006) (26)
A parametrization scheme for classifying models of learnability (1989) (25)
Implementation Issues in the Fourier Transform Algorithm (1995) (24)
Predicting and bypassing end-to-end internet service degradations (2002) (24)
Greedy Packet Scheduling (1990) (23)
Overflow management with multipart packets (2011) (23)
Learning with Maximum-Entropy Distributions (1997) (23)
A Network Creation Game with Nonuniform Interests (2007) (23)
Predicting Counterfactuals from Large Historical Data and Small Randomized Trials (2016) (22)
Adaptive AIMD Congestion Control (2003) (22)
Active sampling for multiple output identification (2006) (21)
Finding the Edge Connectivity of Directed Graphs (1989) (21)
Separating Adaptive Streaming from Oblivious Streaming Using the Bounded Storage Model (2021) (21)
Online Pricing with Strategic and Patient Buyers (2016) (21)
Regret Minimization for Branching Experts (2013) (20)
Many-to-one packet routing on grids (1995) (20)
Buffer overflows of merging streams (2003) (20)
The load‐distance balancing problem (2012) (20)
Online set packing and competitive scheduling of multi-part tasks (2010) (20)
Are Two (Samples) Really Better Than One? (2018) (19)
A Theory of Multiple-Source Adaptation with Limited Target Labeled Data (2020) (19)
Stochastic Shortest Path with Adversarially Changing Costs (2020) (19)
Minimax Regret for Stochastic Shortest Path (2021) (19)
Online Set Packing (2012) (19)
Local computation mechanism design (2013) (19)
Bandits with Movement Costs and Adaptive Pricing (2017) (19)
Sample Complexity of Uniform Convergence for Multicalibration (2020) (19)
Competitive queue management for latency sensitive packets (2008) (18)
Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions (2021) (18)
Competitive ratio vs regret minimization: achieving the best of both worlds (2019) (18)
On the equilibria of alternating move games (2010) (18)
Concentration Bounds for Unigrams Language Model (2005) (18)
Efficient contention resolution protocols for selfish agents (2007) (18)
Strictly-Black-Box Zero-Knowledge and Efficient Validation of Financial Transactions (2012) (18)
Beyond myopic best response (in Cournot competition) (2012) (17)
Adapting to a reliable network path (2003) (17)
Learning Adversarial Markov Decision Processes with Delayed Feedback (2020) (17)
Single Price Mechanisms for Revenue Maximization in Unlimited Supply Combinatorial Auctions (2006) (17)
Multi-Armed Bandits with Metric Movement Costs (2017) (17)
Convergence complexity of optimistic rate based flow control algorithms (extended abstract) (1996) (17)
Efficient PAC Learning from the Crowd (2017) (17)
The Value of Observation for Monitoring Dynamic Systems (2007) (17)
Planning and Learning with Stochastic Action Sets (2018) (16)
Dynamic algorithms against an adaptive adversary: generic constructions and lower bounds (2021) (15)
Source to destination communication in the presence of faults (1989) (15)
Robust Probabilistic Inference (2014) (15)
Learning Valuation Distributions from Partial Observation (2014) (15)
Learning and Domain Adaptation (2009) (15)
Harnessing machine learning to guide phylogenetic-tree search algorithms (2021) (15)
Concentration Bounds for Unigram Language Models (2005) (14)
Competitive dynamic bandwidth allocation (1998) (14)
Greedy packet scheduling on shortest paths (preliminary version) (1991) (14)
Lower bounds on individual sequence regret (2012) (14)
The complexity of approximating the square root (1989) (14)
Harnessing Machine Learning to Improve the Success Rate of Stimuli Generation (2005) (14)
On the bit complexity of distributed computations in a ring with a leader (1986) (13)
Differential pricing with inequity aversion in social networks (2013) (13)
Learning valuation distributions from partial observations (2015) (13)
Differentially Private Multi-Armed Bandits in the Shuffle Model (2021) (13)
Beyond Individual and Group Fairness (2020) (13)
Learning Decision Trees Using the Fourier Sprectrum (Extended Abstract) (1991) (13)
Robust Inference for Multiclass Classification (2018) (12)
Learning Conjunctions with Noise under Product Distributions (1998) (12)
Adversarial Dueling Bandits (2020) (12)
FriendlyCore: Practical Differentially Private Aggregation (2021) (12)
Planning in POMDPs Using Multiplicity Automata (2005) (12)
Discriminative Learning of Prediction Intervals (2017) (12)
Online Learning with Low Rank Experts (2016) (12)
Lower bounds for randomized mutual exclusion (1993) (11)
Thompson Sampling for Complex Bandit Problems (2013) (11)
Fair Leader Election for Rational Agents in Asynchronous Rings and Networks (2018) (11)
Adversarial Online Learning with noise (2018) (11)
Submultiplicative Glivenko-Cantelli and Uniform Convergence of Revenues (2017) (11)
Separating Adaptive Streaming from Oblivious Streaming (2021) (11)
Apprenticeship Learning via Frank-Wolfe (2019) (11)
AdaVegas: adaptive control for TCP Vegas (2003) (11)
Language Complexity on the Synchronous Anonymous Ring (1987) (11)
Reinforcement learning and mistake bounded algorithms (1999) (11)
The intractability of bounded protocols for on-line sequence transmission over non-FIFO channels (1992) (10)
Empirical evaluation of interest-level criteria (1999) (10)
Randomness in private computations (1996) (10)
Competitive router scheduling with structured data (2011) (10)
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity (2020) (10)
Sorting on a Ring of Processors (1990) (10)
Pessimistic decision tree pruning based Continuous-time (1997) (10)
A sufficient condition for truthfulness with single parameter agents (2006) (10)
Differentially-Private Clustering of Easy Instances (2021) (10)
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing (2016) (10)
Constant-Time Local Computation Algorithms (2015) (9)
The Sparse Vector Technique, Revisited (2020) (9)
Average reward reinforcement learning with unknown mixing times (2019) (9)
An Efficient Topology Update Protocol for Dynamic Networks (1992) (9)
Optimal universal learning and prediction of probabilistic concepts (1995) (9)
Optimal Algorithm for Bayesian Incentive-Compatible Exploration (2018) (8)
Pricing Exotic Derivatives Using Regret Minimization (2011) (8)
The intractability of bounded protocols for non-FIFO channels (1989) (8)
Optimal Broadcast with Partial Knowledge (1999) (8)
Robust Option Pricing: Hannan and Blackwell Meet Black and Scholes (2016) (8)
On construction ofk-wise independent random variables (1997) (8)
(In)Stability properties of limit order dynamics (2006) (8)
Improved selection in totally monotone arrays (1993) (7)
Learning What's Going on: Reconstructing Preferences and Priorities from Opaque Transactions (2014) (7)
Oracle-Efficient Regret Minimization in Factored MDPs with Unknown Structure (2020) (7)
Exact Inference of Hidden Structure from Sample Data in noisy-OR Networks (1998) (7)
Quantification of Osteoclasts in Culture, Powered by Machine Learning (2021) (7)
Learning, regret minimization and option pricing (2007) (7)
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback (2022) (7)
Combining online algorithms for rejection and acceptance (2003) (7)
Oracle-Efficient Reinforcement Learning in Factored MDPs with Unknown Structure (2020) (7)
Boosting with Multi-Way Branching in Decision Trees (1999) (7)
Competitive access time via dynamic storage rearrangement (1995) (7)
Ad Exchange - Proposal for a New Trading Agent Competition Game (2012) (7)
Machine Learning Algorithms with Applications in Finance (2014) (6)
Regret Minimization and Convergence to Equilibria in General-sum Markov Games (2022) (6)
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations (2021) (6)
Regret Minimization Algorithms for Pricing Lookback Options (2011) (6)
The computational complexity of universal hash functions (1993) (6)
When Should an Expert Make a Prediction? (2016) (6)
Broadcast with partial knowledge (preliminary version) (1991) (6)
Unknown mixing times in apprenticeship and reinforcement learning (2019) (6)
On Propagating Updates in a Byzantine Environment (1999) (5)
Planning in Hierarchical Reinforcement Learning: Guarantees for Using Local Policies (2019) (5)
Improved Generalization Bounds for Adversarially Robust Learning (2018) (5)
Efficient Co-Training of Linear Separators under Weak Dependence (2017) (5)
The price of uncertainty (2009) (5)
Regret Minimization and Job Scheduling (2009) (5)
Adversarial Stochastic Shortest Path (2020) (5)
A Tight Bound for Approximating the Square Root (1997) (5)
Fast exponentiation using the truncation operation (1992) (5)
Repeated Budgeted Second Price Ad Auction (2011) (5)
Asymptotic Active Learning (2007) (5)
Local Computation Mechanism Design (2013) (5)
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation (2022) (5)
Modeling Attrition in Recommender Systems with Departing Bandits (2022) (4)
Online Markov Decision Processes with Aggregate Bandit Feedback (2021) (4)
Reinforcement Learning with Feedback Graphs (2020) (4)
Learning Efficiently Function Approximation for Contextual MDP (2022) (4)
Local Cycle Generation in Multihop Radio Networks (1987) (4)
Benign Underfitting of Stochastic Gradient Descent (2022) (4)
Competitive on-line paging strategies for mobile users under delay constraints (2004) (4)
Optimal Rates for Random Order Online Optimization (2021) (4)
Sublinear Graph Augmentation for Fast Query Implementation (2018) (4)
Differentially Private Learning of Geometric Concepts (2019) (4)
Probe scheduling for efficient detection of silent failures (2013) (4)
Regret Minimization , and Equilibria (4)
Bit Complexity of Order Statistics on a Distributed Star Network (1989) (4)
Dynamics of Evolving Social Groups (2016) (4)
Combining Online Algorithms for Acceptance and Rejection (2005) (4)
Learning with Global Cost in Stochastic Environments (2010) (3)
A Characterization of Semi-Supervised Adversarially-Robust PAC Learnability (2022) (3)
Improved combination of online algorithms for acceptance and rejection (2004) (3)
Flow Equilibria via Online Surge Pricing (2018) (3)
Scheduling multipacket frames with frame deadlines (2015) (3)
Nash Convergence of Gradient Dynamics in Iterated General-Sum Games (2013) (3)
Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP (2022) (3)
Optimal Algorithm for Bayesian Incentive-Compatible (2018) (3)
Strategizing against Learners in Bayesian Games (2022) (3)
Combinatorial Bandits with Full-Bandit Feedback: Sample Complexity and Regret Minimization (2019) (3)
On Lotteries with Unique Winners (1995) (3)
Learning to Screen (2019) (3)
On Learning Conjunctions with Malicious Noise (1996) (3)
Dueling Convex Optimization (2021) (3)
Sponsored Search Auction Design via Machine Learning (2008) (3)
Dynamics of Evolving Social Groups (2019) (2)
Kidney exchange and endless paths: On the optimal use of an altruistic donor (2020) (2)
A User Re-Modeling Approach to Item Recommendation using Complex Usage Data (2017) (2)
Optimal Smoothing S hedules for Real-Time Streams EXTENDED (2000) (2)
Are All Experts Equally Good? A Study of Analyst Earnings Estimates (2018) (2)
Are Two (Samples) Really Better Than One? On the Non-Asymptotic Performance of Empirical Revenue Maximization (2018) (2)
ROI Maximization in Stochastic Online Decision-Making (2019) (2)
QoS-Competitive Video Buffering (2001) (2)
Online revenue maximization for server pricing (2019) (2)
Computational Game Theory 8.1 External Regret -reminder (2010) (2)
On-line Markov Decision Processes (2006) (2)
Competitive ratio versus regret minimization: achieving the best of both worlds (2019) (2)
Designing Committees for Mitigating Biases (2020) (2)
The AND-OR Game: Equilibrium Characterization - (Working Paper) (2012) (2)
Automatic Representation for Lifetime Value Recommender Systems (2017) (2)
Polynomial End-To-End Communication (Extended Abstract) (1989) (2)
Harnessing machine learning to improve the success rate of stimuli generation (2006) (2)
1 Extensive Games with Perfect Information (2004) (1)
Uniswap Liquidity Provision: An Online Learning Approach (2023) (1)
The Strategy of Experts for Repeated Predictions (2017) (1)
G T ] 1 J ul 2 01 8 Bayesian Exploration : Incentivizing Exploration in Bayesian Games * (2018) (1)
Thompson Sampling for Adversarial Bit Prediction (2019) (1)
On the Convergence of Rate Based Flow ControlYehuda (1995) (1)
Message authentication method and communication system (1994) (1)
Convergence complexity of optimistic rate based flow control algorithms (brief announcement) (1996) (1)
Computational Learning Theory Spring Semester , 2009 / 10 Lecture 11 : Sponsored search (2010) (1)
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, COLT 1998, Madison, Wisconsin, USA, July 24-26, 1998 (1998) (1)
A LASSO-based approach to sample sites for phylogenetic tree search (2022) (1)
Actor-critic Algorithms 1. Policy Gradient Methods for Reinforcement Learning with Function Average Reward Td Actor-critic Algorithm Using Func- Tion Approximation (1)
Space Eecient Fair Queuing by Stochastic Memory Multiplexing (1997) (1)
Improved Selection on Totally Monotone Arrays (1991) (1)
On Hannan and Blackwell's Approachability and Options - A Game Theoretic Approach for Option Pricing (2006) (1)
Hierarchical Reinforcement Learning: Approximating Optimal Discounted TSP Using Local Policies (2018) (1)
Lower bounds on individual sequence regret (2015) (1)
Scheduling multipacket frames with frame deadlines (2017) (1)
Lecture 5 : Lower Bounds using Information Theory Tools (2011) (1)
Graph-based Discriminators: Sample Complexity and Expressiveness (2019) (1)
A Model-Free Approach for a TAC-AA Trading Agent (2012) (1)
A CONSTRUCTION OF A CIPHER FROM A (1991) (1)
Monotone Learning (2022) (1)
Learning Decision Trees with Stochastic Linear Classifiers (2018) (1)
On Price versus Quality (2018) (1)
Fair Wrapping for Black-box Predictions (2022) (1)
Online Allocation and Pricing with Economies of Scale (2015) (1)
Cooperative Online Learning in Stochastic and Adversarial MDPs (2022) (1)
Counterfactual Optimism: Rate Optimal Regret for Stochastic Contextual MDPs (2022) (1)
Scheduling Subset Tests: One-Time, Continuous, and How They Relate (2013) (1)
Regret minimization of Tabular Policy Gradient (2022) (0)
Learning Revenue Maximization using Posted Prices for Stochastic Strategic Patient Buyers (2022) (0)
2.1 Coordination Ratio (2004) (0)
There is no Accuracy-Interpretability Tradeoff in Reinforcement Learning for Mazes (2022) (0)
Proof: Let N = (1996) (0)
7.1 Extensive Games with Perfect Information (2006) (0)
Virtual-credit: Efficient end-to-end credit based flow control (1997) (0)
On Differentially Private Online Predictions (2023) (0)
Repeated A/B Testing (2019) (0)
A New Theoretical Framework for Fast and Accurate Online Decision-Making (2021) (0)
Optimistic-Conservative Bidding in Sequential Auctions (2015) (0)
Finding Safe Zones of policies Markov Decision Processes (2022) (0)
5.1 Introduction 5.2 Proof of Existence of Stochastic Nash Equilib- Rium in Any Game 5.2.1 Proof Outline (2004) (0)
Label Efficient Learning by Exploiting Multi-Class Output Codes (2015) (0)
Software ENgineering Improved Competitive Guarantees for QoS Buffering (2003) (0)
Concurrent Shuffle Differential Privacy Under Continual Observation (2023) (0)
Benign Underfitting of SGD in Stochastic Convex Optimization (2022) (0)
Many-to-one packet routing on grids (Extended Abstract). (1995) (0)
Implemeting the ” Wisdom of the Crowd ” ∗ (2012) (0)
1 0 Ju l 2 01 4 Learning Valuation Distributions from Partial Observation (2015) (0)
Electronic Markets and Auctions (Dagstuhl Seminar 13461) (2013) (0)
Adaptive AIMD Congestion Control 1 (0)
Certificat d'echange pour validation unidirectionnelle d'informations (1994) (0)
Repeated Budgeted Second Price Ad Auction (2013) (0)
Efficient On-line Call Control Algorithms (Extended Abstract) (1993) (0)
8.1 Regret 8.2 Basic Model 8.3 a Greedy Algorithm (2004) (0)
An empirical study of trading agent robustness (2013) (0)
Appendices for the paper Thompson Sampling for Complex Online Problems – (2014) (0)
History-Independent Distributed Multi-agent Learning (2016) (0)
Lecture 2: March 1 2010 (2010) (0)
Online Learning versus Ooine Learning (2007) (0)
Efficient PAC Learning from the Crowd Pranjal Awasthi (2017) (0)
Adaptive Control for TCP (2002) (0)
Robust Inference and Local Algorithms (2015) (0)
Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation (2023) (0)
On the geometry of output-code multi-class learning (2015) (0)
Lecture 3 : Price of Anarchy ( PoA ) : Routing (2006) (0)
Pseudonorm Approachability and Applications to Regret Minimization (2023) (0)
The AND-OR Game (2016) (0)
Advanced Topics in Machine Learning and Algorithmic Game Theory Lecture 7 : Bayesian approach to MAB-Gittins index (2011) (0)
Constant-Time Local Computation Algorithms (2017) (0)
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback (2023) (0)
Dueling Convex Optimization with General Preferences (2022) (0)
Learning and Generalization for Matching Problems (2019) (0)
Competitive Access Time via Dynamic Storage Rearrangement (Preliminary Version). (1995) (0)
Computational Game Theory Spring Semester , 2009 / 10 Lecture 10 : Mechanism Design (2010) (0)
Ciphering method and device (1994) (0)
Stochastic Strategic Patient Buyers: Revenue maximization using posted prices (2022) (0)
Robust domain adaptation (2013) (0)
Optimal Broadcast with Partial Knowledge (Extended Abstract) (1995) (0)
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation (2023) (0)
The Complexity of Approximating the Square Root (Extended Summary) (1989) (0)
6.2 Existence Theorem 6.2.1 Model and Notations (2006) (0)
Machine Learning: Foundations Decision Trees 12.1 Decision Tree: Building 12.1.1 Introduction (2011) (0)
Buffer Over owManagement in QoS Swit hes (2000) (0)
The tree reconstruction game: phylogenetic reconstruction using reinforcement learning (2023) (0)
Game Theory Meets Computational Learning Theory (Dagstuhl Seminar 17251) (2017) (0)
Fast and Accurate Repeated Decision Making (2020) (0)
Competitive Access Time via Dynamic Storage (1995) (0)
Dueling Bandits with Team Comparisons (2021) (0)
Fast and Accurate Repeated Decision Making (2020) (0)
Learning What’s Going on (2018) (0)
Competitive Equilibria with Unequal Budgets: Supporting Arbitrary Pareto Optimal Allocations (2021) (0)
On Regret and Options-A Game Theoretic Approach for Option Pricing † (2005) (0)
Eluder-based Regret for Stochastic Contextual MDPs (2022) (0)
Differentially-Private Bayes Consistency (2022) (0)
What killed the Convex Booster ? (2022) (0)
Regret Minimization 2 Full Information Model 3 External Regret (2010) (0)
Dec . 8 , 2017 Learning in the Presence of Strategic Behavior (0)
Decision Tree : Pruning 12 . 1 . 1 Why Pruning ? (2014) (0)
Exploration Strategies for Model-based Learning 37 Convergence Results for Single-step On-policy Reinforcement-learning Algorithms. Machine Learning Journal Exploration Strategies for Model-based Learning Exploration Strategies for Model-based Learning (2007) (0)
L G ] 2 8 M ay 2 01 9 Repeated A / B Testing Nicolò Cesa-Bianchi Tommaso R . Cesari (2019) (0)
Keyword Optimization in Search-Based Advertising Markets (2011) (0)
Model-Free RL (2023) (0)
On the complexity of computing algebraic functions (1990) (0)
Harnessing machine learning to boost heuristic strategies for phylogenetic-tree search (2020) (0)

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