Vapnik-Chervonenkis dimension of neural networks
The handbook of brain theory and neural networks
Competitive auctions and digital goods
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Competitive generalized auctions
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Learning in Neural Networks: Theoretical Foundations
Learning in Neural Networks: Theoretical Foundations
Online learning in online auctions
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Competitive Auctions for Multiple Digital Goods
ESA '01 Proceedings of the 9th Annual European Symposium on Algorithms
From optimal limited to unlimited supply auctions
Proceedings of the 6th ACM conference on Electronic commerce
Collusion-resistant mechanisms for single-parameter agents
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
On profit-maximizing envy-free pricing
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Near-optimal pricing in near-linear time
WADS'05 Proceedings of the 9th international conference on Algorithms and Data Structures
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Approximation algorithms and online mechanisms for item pricing
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Algorithmic pricing via virtual valuations
Proceedings of the 8th ACM conference on Electronic commerce
Matroids, secretary problems, and online mechanisms
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Designing and learning optimal finite support auctions
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Mechanism design, machine learning, and pricing problems
ACM SIGecom Exchanges
Incentive compatible regression learning
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Dynamic cost-per-action mechanisms and applications to online advertising
Proceedings of the 17th international conference on World Wide Web
Optimal mechanism design and money burning
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
Item pricing for revenue maximization
Proceedings of the 9th ACM conference on Electronic commerce
Better redistribution with inefficient allocation in multi-unit auctions with unit demand
Proceedings of the 9th ACM conference on Electronic commerce
Towards a theory of incentives in machine learning
ACM SIGecom Exchanges
The adwords problem: online keyword matching with budgeted bidders under random permutations
Proceedings of the 10th ACM conference on Electronic commerce
On random sampling auctions for digital goods
Proceedings of the 10th ACM conference on Electronic commerce
Strategyproof classification under constant hypotheses: a tale of two functions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
On Stackelberg Pricing with Computationally Bounded Consumers
WINE '09 Proceedings of the 5th International Workshop on Internet and Network Economics
Bundle pricing with comparable items
ESA'07 Proceedings of the 15th annual European conference on Algorithms
A theory of loss-leaders: making money by pricing below cost
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
Pricing commodities, or how to sell when buyers have restricted valuations
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
Theoretical Computer Science
The power of uncertainty: bundle-pricing for unit-demand customers
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Proceedings of the 12th ACM conference on Electronic commerce
Black-box reductions in mechanism design
APPROX'11/RANDOM'11 Proceedings of the 14th international workshop and 15th international conference on Approximation, randomization, and combinatorial optimization: algorithms and techniques
Approximately optimal mechanism design via differential privacy
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
On the competitive ratio of the random sampling auction
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Algorithms for strategyproof classification
Artificial Intelligence
Proceedings of the 13th ACM Conference on Electronic Commerce
Optimal bundle pricing with monotonicity constraint
Operations Research Letters
Buying Cheap Is Expensive: Approximability of Combinatorial Pricing Problems
SIAM Journal on Computing
Selling in Exclusive Markets: Some Observations on Prior-Free Mechanism Design
ACM Transactions on Economics and Computation - Special Issue on Algorithmic Game Theory
ACM SIGecom Exchanges
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We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a wide variety of revenue-maximizing pricing problems. Our reductions imply that for these problems, given an optimal (or \beta-approximation) algorithm for the standard algorithmic problem, we can convert it into a (1+ \in)-approximation (or \beta(1+ \in)-approximation) for the incentive-compatiblemechanism design problem, so long as the number of bidders is sufficiently large as a function of an appropriate measure of complexity of the comparison class of solutions. We apply these results to the problem of auctioning a digital good, the attribute auction problem, and to the problem of itempricing in unlimited-supply combinatorial auctions. From a learning perspective, these settings present several challenges: in particular, the loss function is discontinuous and asymmetric, and the range of bidders驴 valuations may be large.