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06/26/2023
Off-Policy Evaluation of Ranking Policies under Diverse User Behavior
Ranking interfaces are everywhere in online platforms. There is thus an ...
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05/14/2023
Off-Policy Evaluation for Large Action Spaces via Conjunct Effect Modeling
We study off-policy evaluation (OPE) of contextual bandit policies for l...
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11/25/2022
Policy-Adaptive Estimator Selection for Off-Policy Evaluation
Off-policy evaluation (OPE) aims to accurately evaluate the performance ...
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06/15/2022
Fair Ranking as Fair Division: Impact-Based Individual Fairness in Ranking
Rankings have become the primary interface in two-sided online markets. ...
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02/23/2022
A Real-World Implementation of Unbiased Lift-based Bidding System
In display ad auctions of Real-Time Bid-ding (RTB), a typical Demand-Sid...
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02/13/2022
Off-Policy Evaluation for Large Action Spaces via Embeddings
Off-policy evaluation (OPE) in contextual bandits has seen rapid adoptio...
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02/03/2022
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
In real-world recommender systems and search engines, optimizing ranking...
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09/17/2021
Data-Driven Off-Policy Estimator Selection: An Application in User Marketing on An Online Content Delivery Service
Off-policy evaluation (OPE) is the method that attempts to estimate the ...
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09/17/2021
Accelerating Offline Reinforcement Learning Application in Real-Time Bidding and Recommendation: Potential Use of Simulation
In recommender systems (RecSys) and real-time bidding (RTB) for online a...
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08/31/2021
Evaluating the Robustness of Off-Policy Evaluation
Off-policy Evaluation (OPE), or offline evaluation in general, evaluates...
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10/21/2020
Optimal Off-Policy Evaluation from Multiple Logging Policies
We study off-policy evaluation (OPE) from multiple logging policies, eac...
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08/17/2020
A Large-scale Open Dataset for Bandit Algorithms
We build and publicize the Open Bandit Dataset and Pipeline to facilitat...
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07/08/2020
Unbiased Lift-based Bidding System
Conventional bidding strategies for online display ad auction heavily re...
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06/18/2020
Multi-Source Unsupervised Hyperparameter Optimization
How can we conduct efficient hyperparameter optimization for a completel...
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10/16/2019
Unsupervised Domain Adaptation Meets Offline Recommender Learning
To construct a well-performing recommender offline, eliminating selectio...
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10/04/2019
Dual Learning Algorithm for Delayed Feedback in Display Advertising
In display advertising, predicting the conversion rate, that is, the pro...
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09/11/2019
Counterfactual Cross-Validation: Effective Causal Model Selection from Observational Data
What is the most effective way to select the best causal model among pot...
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09/09/2019