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Found 12 papers, 2 papers with code
Optimal Non-parametric Learning in Repeated Contextual Auctions with Strategic Buyer
We study learning algorithms that optimize revenue in repeated contextual posted-price auctions where a seller interacts with a single strategic buyer that seeks to maximize his cumulative discounted surplus.
Bisection-Based Pricing for Repeated Contextual Auctions against Strategic Buyer
We are interested in learning algorithms that optimize revenue in repeated contextual posted-price auctions where a single seller faces a single strategic buyer.
Crowdsourcing Natural Language Data at Scale: A Hands-On Tutorial
In this tutorial, we present a portion of unique industry experience in efficient natural language data annotation via crowdsourcing shared by both leading researchers and engineers from Yandex.
Finite-State Extreme Effect Variable
We generalize to the finite-state case the notion of the extreme effect variable $Y$ that accumulates all the effect of a variant variable $V$ observed in changes of another variable $X$.
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer
We study revenue optimization pricing algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation.
Reserve Pricing in Repeated Second-Price Auctions with Strategic Bidders
We study revenue optimization learning algorithms for repeated second-price auctions with reserve where a seller interacts with multiple strategic bidders each of which holds a fixed private valuation for a good and seeks to maximize his expected future cumulative discounted surplus.
Aggregation of pairwise comparisons with reduction of biases
Answers to pairwise tasks are known to be affected by the position of items on the screen, however, previous models for aggregation of pairwise comparisons do not focus on modeling such kind of biases.
Weakly Consistent Optimal Pricing Algorithms in Repeated Posted-Price Auctions with Strategic Buyer
We study revenue optimization learning algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation for a good and seeks to maximize his cumulative discounted surplus.
On consistency of optimal pricing algorithms in repeated posted-price auctions with strategic buyer
Finally, we generalize results on strategic regret previously known for geometric discounting of the buyer's surplus to discounting of other types, namely: the optimality of the pricing PRRFES to the case of geometrically concave decreasing discounting; and linear lower bound on the strategic regret of a wide range of horizon-independent weakly consistent algorithms to the case of arbitrary discounts.
User Model-Based Intent-Aware Metrics for Multilingual Search Evaluation
We develop a novel approach to build intent-aware user behavior models, which overcome these limitations and convert to quality metrics that better correlate with standard online metrics of user satisfaction.
Efficient High-Order Interaction-Aware Feature Selection Based on Conditional Mutual Information
This study introduces a novel feature selection approach CMICOT, which is a further evolution of filter methods with sequential forward selection (SFS) whose scoring functions are based on conditional mutual information (MI).
Prediction of Video Popularity in the Absence of Reliable Data from Video Hosting Services: Utility of Traces Left by Users on the Web
We investigate video popularity prediction based on features from three primary sources available for a typical operating company: first, the content hosting provider may deliver its data via its API, second, the operating company makes use of its own search and browsing logs, third, the company crawls information about embeds of a video and links to a video page from publicly available resources on the Web.
