Learning to Top-K Search using Pairwise Comparisons

No abstract is available for this paper.

• Publication year

  2013

• Venue

  International Conference on Artificial Intelligence and Statistics

• Publication date

  2013-04-29

• Fields of study

  Mathematics, Computer Science

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Inference

  2020cited by this paper
• Efficient rank aggregation using partial data

  2012cited by this paper
• Comparison-Based Learning with Rank Nets

  2012cited by this paper
• The Asymptotics of Ranking Algorithms

  2012cited by this paper
• Active Ranking using Pairwise Comparisons

  2011influential reference
• An Active Learning Algorithm for Ranking from Pairwise Preferences with an Almost Optimal Query Complexity

  2010cited by this paper
• Searching protein structure databases with DaliLite v.3

  2008cited by this paper
• Learning to rank: from pairwise approach to listwise approach

  2007cited by this paper
• The Netflix Prize

  2007cited by this paper
• Noisy sorting without resampling

  2007cited by this paper
• Noisy binary search and its applications

  2007cited by this paper
• Robust Reductions from Ranking to Classification

  2006cited by this paper
• Rank aggregation methods for the Web

  2001cited by this paper
• Conformant Planning via Symbolic Model Checking

  2000cited by this paper

• Interactive Search with Reinforcement Learning

  2025cites this paper
• PAL: Sample-Efficient Personalized Reward Modeling for Pluralistic Alignment

  2025cites this paper
• Learn to Rank Risky Investors: A Case Study of Predicting Retail Traders’ Behaviour and Profitability

  2025cites this paper
• Robust Best Point Selection under Unreliable User Feedback

  2024cites this paper
• Learning Populations of Preferences via Pairwise Comparison Queries

  2024cites this paper
• PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences

  2024cites this paper
• Thompson Sampling Procedures for Ranking and Selection with Pairwise Comparisons and Binary Outcomes

  2024cites this paper
• Carrot and Stick: Eliciting Comparison Data and Beyond

  2024cites this paper
• Finding Best Tuple via Error-prone User Interaction

  2023cites this paper
• Crowdsourcing of labeling image objects: an online gamification application for data collection

  2023cites this paper
• Interactive Search with Mixed Attributes

  2023cites this paper
• Integrating Rankings into Quantized Scores in Peer Review

  2022cites this paper
• Interactive Mining with Ordered and Unordered Attributes

  2022influential citation
• Interactive Search for One of the Top-k

  2021influential citation
• The Picasso Algorithm for Bayesian Localization Via Paired Comparisons in a Union of Subspaces Model

  2020cites this paper
• Simultaneous Preference and Metric Learning from Paired Comparisons

  2020cites this paper
• Online Top-K Selection in Crowdsourcing Environments

  2020cites this paper
• A General Early-Stopping Module for Crowdsourced Ranking

  2019cites this paper
• Top-κ selection with pairwise comparisons

  2019influential citation
• Pcard: Personalized Restaurants Recommendation from Card Payment Transaction Records

  2019cites this paper
• A Human-in-the-loop Attribute Design Framework for Classification

  2019cites this paper
• Active Embedding Search via Noisy Paired Comparisons

  2019cites this paper
• Hidden POI Ranking with Spatial Crowdsourcing

  2019cites this paper
• Joint Estimation of Trajectory and Dynamics from Paired Comparisons

  2019cites this paper
• Comparison Based Learning from Weak Oracles

  2018cites this paper
• Crowd-Powered Data Mining

  2018cites this paper
• Climate change learning in an electricity utility: distribution division case study, Eskom, South Africa.

  2018cites this paper
• As you like it: Localization via paired comparisons

  2018cites this paper
• A Rating-Ranking Method for Crowdsourced Top-k Computation

  2018cites this paper
• Instance-Optimality in the Noisy Value-and Comparison-Model - Accept, Accept, Strong Accept: Which Papers get in?

  2018cites this paper
• Crowdsourced Data Management

  2018influential citation
• Optimal Instance Adaptive Algorithm for the Top- $K$ Ranking Problem

  2018cites this paper
• Approximate Ranking from Pairwise Comparisons

  2018cites this paper
• Top-k Sorting Under Partial Order Information

  2018cites this paper
• A partial-order-based framework for cost-effective crowdsourced entity resolution

  2018cites this paper
• Managing the quality of crowdsourced databases

  2017cites this paper
• Learning From People

  2017cites this paper
• Crowdsourced Data Management: Overview and Challenges

  2017influential citation
• Competitive analysis of the top-K ranking problem

  2016cites this paper
• Multiresolution analysis of ranking data

  2016cites this paper
• Top-K Ranking from Pairwise Comparisons: When Spectral Ranking is Optimal

  2016cites this paper
• Crowdsourced Top-k Algorithms: An Experimental Evaluation

  2016cites this paper
• Active Ranking from Pairwise Comparisons and the Futility of Parametric Assumptions

  2016cites this paper
• Active ranking from pairwise comparisons and when parametric assumptions do not help

  2016cites this paper
• Crowdsourced Data Management: A Survey

  2016cites this paper
• Active top-K ranking from noisy comparisons

  2016cites this paper
• Parallel algorithms for select and partition with noisy comparisons

  2016cites this paper
• Optimization of Orchestration of Geocrowdsourcing Activities

  2016cites this paper
• Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons

  2015cites this paper
• Simple, Robust and Optimal Ranking from Pairwise Comparisons

  2015cites this paper
• PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences

  2014cites this paper
• S AMPLE -E FFICIENT

  year unknowncites this paper