The Analysis of Permutations

Cited by (732)

Items 401–500 of 732

1. Optimizing Positional Scoring Rules for Rank Aggregation
   Ioannis Caragiannis, Xenophon Chatzigeorgiou, George A. Krimpas, Alexandros A. Voudouris · 2017 · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI))
2. A Note on Ranking in the Plackett-Luce Model for Multiple Comparisons
   Jing Luo, Hong Qin · 2019 · Acta Mathematicae Applicatae Sinica English Series
3. Learning Modulo Theories for constructive preference elicitation
   Paolo Campigotto, Stefano Teso, Roberto Battiti, Andrea Passerini · 2021 · Artificial Intelligence
4. Efficient and Accurate Learning of Mixtures of Plackett-Luce Models
   Duc Nguyen, Anderson Y. Zhang · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
5. The MNL-Bandit Problem: Theory and Applications
   Vashist Avadhanula · 2019
6. Pareto-Optimal Fairness-Utility Amortizations in Rankings with a DBN Exposure Model
   Till Kletti, Jean-Michel Renders, Patrick Loiseau · 2022 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
7. Active Evaluation: Efficient NLG Evaluation with Few Pairwise Comparisons
   Akash Kumar Mohankumar, Mitesh M. Khapra · 2022 · Proceedings of the conference - Association for Computational Linguistics. Meeting
8. Experimental Studies of Human Behavior in Social Computing Systems
   Qiushi Mao · 2015
9. A Model-Based Approach for Qualitative Assessment in Opinion Mining
   Maria Iannario, Domenico Piccolo · 2012 · Studies in classification, data analysis, and knowledge organization
10. Unsupervised Learning to Rank Aggregation using Parameterized Function Optimization
    Amirhossein Tavanaei, Raju Gottumukkalay, Anthony S. Maida, Vijay V. Raghavan · 2018 · International Joint Conference on Neural Networks (IJCNN)
11. Balancing the Diversification-Intensification Trade-off Using Mixtures of Probability Models
    Joan Alza, Josu Ceberio, Borja Calvo · 2018 · IEEE Congress on Evolutionary Computation (CEC)
12. Sampling and learning the Mallows and Weighted Mallows models under the Hamming distance
    Ekhiñe Irurozki, Borja Calvo Molinos, Jose Antonio Lozano · 2014 · Communities in ADDI (Universidad del Pais Vasco)
13. Investigating Consumer Food Waste Decisions: A Cross-country Comparison between Thailand and the United Kingdom
    Ponjan Pinpart, Daniele Asioli, Kelvin Balcombe · 2019 · RePEc: Research Papers in Economics
14. Preference Modeling with Context-Dependent Salient Features
    Amanda Bower, Laura Balzano · 2020 · arXiv (Cornell University)
15. Learning to Price Under Competition for Multinomial Logit Demand
    Vineet Goyal, Shukai Li, Sanjay Mehrotra · 2023 · SSRN Electronic Journal
16. Breaking the Top- K Barrier: Advancing Top- K Ranking Metrics Optimization in Recommender Systems
    Weiqin Yang, Jiawei Chen, Shengjia Zhang, Peng Wu, Yuegang Sun, Yan Feng, Chun Chen, Can Wang · 2025 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
17. A Self-Distilled Learning to Rank Model for Ad Hoc Retrieval
    Sanaz Keshvari, Farzan Saeedi, Hadi Sadoghi Yazdi, Faezeh Ensan · 2024 · ACM Transactions on Information Systems
18. Models and Rating Systems for Head-to-Head Competition
    Mark E. Glickman, Albyn C. Jones · 2024 · Annual Review of Statistics and Its Application
19. A MATHEMATICAL ANALYSIS OF THE INCLUSION OF INSTITUTIONAL BETTING FUNDS INTO STOCK MARKET: THE CASE OF TECHNICAL AND FUNDAMENTAL PAYOFF MODELS IN HORSERACE BETTING
    Craig George Leslie Hopf, Gurudeo Anand Tularam · 2014 · Journal of Mathematics and Statistics
20. Listwise Learning to Rank from Crowds
    Ou Wu, Qiang You, Fen Xia, Lei Ma, Weiming Hu · 2016 · ACM Transactions on Knowledge Discovery from Data
21. Finding Convincing Arguments Using Scalable Bayesian Preference Learning
    Edwin Simpson, Iryna Gurevych · 2018 · Transactions of the Association for Computational Linguistics
22. On Bayesian inference for the Extended Plackett-Luce model
    Stephen R. Johnson, Daniel A. Henderson, Richard J. Boys · 2021 · Bayesian Analysis
23. Dynamic Pricing and Assortment Under a Contextual MNL Demand
    Noémie Périvier, Vineet Goyal · 2022 · neural information processing systems
24. Generalizing the Elo rating system for multiplayer games and races: why endurance is better than speed
    Ben Powell · 2023 · Journal of Quantitative Analysis in Sports
25. Estimating the ordering of variables in a VAR using a Plackett–Luce prior
    Wu Ping, Gary M. Koop · 2023 · Economics Letters
26. Plackett–Luce modeling with trajectory models for measuring athlete strength
    Katy McKeough, Mark E. Glickman · 2023 · Journal of Quantitative Analysis in Sports
27. The Least Increasing Aversion (LIA) Protocol: Illustration on Identifying Individual Susceptibility to Cybersickness Triggers
    Nana Tian, Ronan Boulic · 2024 · IEEE Transactions on Visualization and Computer Graphics
28. How Engineering Students Learn and are Impacted by Empathy Training: A Multi-year Study of an Empathy Program Focused on Disability and Technology
    Eric M. Schearer, Cameron J LaMack, Hannah LaMack · 2025 · Biomedical Engineering Education
29. Ranking Distributions based on Noisy Sorting.
    Adil El Mesaoudi-Paul, Eyke Hüllermeier, Róbert Busa‐Fekete · 2018 · Open access LMU (Ludwid Maxmilian's Universitat Munchen)
30. Clustering-Based Transductive Semi-Supervised Learning for Learning-to-Rank
    Ashwini Rahangdale, Shital Raut · 2019 · International Journal of Pattern Recognition and Artificial Intelligence
31. Language Modelling via Learning to Rank
    Arvid Frydenlund, Gagandeep Singh, Frank Rudzicz · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
32. Transfer Learning for Information Retrieval
    Pengfei Li · 2015 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
33. Ranking Optimization with Constraints
    Fangzhao Wu, Jun Xu, Hang Li, Xin Jiang · 2014 · ACM International Conference on Information and Knowledge Management (CIKM)
34. Place probabilities in normal order statistics models for horse races
    Robert J. Henery · 1981 · Journal of Applied Probability
35. Ranking and unranking permutations with applications
    F. Critani, Marco Dall'aglio, Giuseppe Di Biase · 1997
36. Contrastive learning from pairwise measurements
    Yi Chen, Zhuoran Yang, Yuchen Xie, Zhaoran Wang · 2018 · Rare & Special e-Zone (The Hong Kong University of Science and Technology)
37. Generalized transitivity: A systematic comparison of concepts with an application to preferences in the Babington Smith model
    Björn Haddenhorst, Eyke Hüllermeier, Martin Kolb · 2020 · International Journal of Approximate Reasoning
38. Estimation of Skill Distribution from a Tournament
    Ali Jadbabaie, Anuran Makur, Devavrat Shah B · 2020 · neural information processing systems
39. Neural methods for effective, efficient, and exposure-aware information retrieval
    Bhaskar Mitra · 2021 · ACM SIGIR Forum
40. MNL-Bandit with Knapsacks
    Abdellah Aznag, Vineet Goyal, Noémie Périvier · 2021 · ACM Conference on Economics and Computation (EC)
41. Certainty-based Preference Completion
    Lei Li, Minghe Xue, Zan Zhang, Huanhuan Chen, Xindong Wu · 2022 · Data Intelligence
42. Reconciling real scores with binary comparisons: a unified logistic model for ranking
    Nir Ailon · 2008
43. Probabilistic Inference Over Repeated Insertion Models
    Batya Kenig, Lovro Ilijašić, Haoyue Ping, Benny Kimelfeld, Julia Stoyanovich · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
44. Multinomial Logit Contextual Bandits
    Min-hwan Oh, Garud Iyengar · 2019
45. Multiresolution Analysis of Incomplete Rankings
    Stéphan Clémençon, Jérémie Jakubowicz, Eric Sibony · 2014 · arXiv (Cornell University)
46. Probabilistic Zero-shot Classification with Semantic Rankings
    Jihun Hamm, Mikhail Belkin · 2015 · arXiv (Cornell University)
47. Choice by Elimination via Deep Neural Networks
    Truyen Tran, Dinh Phung, Svetha Venkatesh · 2016 · arXiv (Cornell University)
48. Integrating Empirical Estimation and Assortment Personalization for E-Commerce: A Consider-Then-Choose Model
    Maggie (Manqi) Li, Xiang Liu, Yan Hua Huang, Cong Shi · 2018 · SSRN Electronic Journal
49. Consequential Ranking Algorithms and Long-term Welfare
    Behzad Tabibian, Vicenç Gómez, Abir De, Bernhard Schölkopf, Manuel Gomez-Rodriguez · 2019 · arXiv (Cornell University)
50. A Nonparametric Approach to Modeling Choice with Limited Data
    Vivek F. Farias, Srikanth Jagabathula, Devavrat Shah B · 2009 · arXiv (Cornell University)
51. Preselection Bandits under the Plackett-Luce Model.
    Viktor Bengs, Eyke Hüllermeier · 2019 · arXiv (Cornell University)
52. A Generalized Markov Chain Model to Capture Dynamic Preferences and Choice Overload
    Kumar Goutam, Vineet Goyal, Agathe Soret · 2019 · RePEc: Research Papers in Economics
53. Learning Mixtures of Plackett-Luce Models with Features from Top-$l$ Orders.
    Zhibing Zhao, Lirong Xia · 2020 · arXiv (Cornell University)
54. The Refined Assortment Optimization Problem
    Gerardo Berbeglia, Álvaro Flores, Guillermo Gallego · 2021 · RePEc: Research Papers in Economics
55. Randomized Assortment Optimization
    Zhengchao Wang, Heikki Peura, Wolfram Wiesemann · 2020 · SSRN Electronic Journal
56. Individually Fair Ranking
    Amanda Bower, Hamid Eftekhari, Mikhail Yurochkin, Yuekai Sun · 2021 · arXiv (Cornell University)
57. Assortment Optimization under the Multi-Purchase Multinomial Logit Choice Model
    Jacob Feldman, Danny Segev, Hüseyin Topaloğlu, Laura Wagner, Yicheng Bai · 2021 · SSRN Electronic Journal
58. Automatic recognition of engagement and emotion in a group of children
    Jaebok Kim · 2018
59. Learning Mixed Multinomial Logits with Provable Guarantees and its Applications in Multi-product Pricing
    Yiqun Hu, David Simchi‐Levi, Zhenzhen Yan · 2023 · SSRN Electronic Journal
60. PlackettLuce: Plackett-Luce Models for Rankings
    Heather Turner, Ioannis Kosmidis, David Firth · 2017
61. Bidding for Talent: A Test of Conduct in a High-Wage Labor Market
    Nina Roussille, Benjamin Scuderi · 2025 · National Bureau of Economic Research
62. Top-k Ranking Bayesian Optimization
    Quoc Phong Nguyen, Sebastian Shenghong Tay, Bryan Kian Hsiang Low, Patrick Jaillet · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
63. Improving the aggregation and evaluation of NBA mock drafts
    Jared D. Fisher, Colin Montague · 2024 · Journal of Quantitative Analysis in Sports
64. Response Generation through Social Reasoning in Large Language Models with Direct Diverse Preferences Optimization
    Maryam Amirizaniani, Elias Martin, Afra Mashhadi, Chirag Suresh Shah · 2025 · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR)
65. Resident recovery priorities for activities and services after a hypothetical hurricane: Insights from metropolitan survey data
    Jiayun Shen, Pamela M. Murray‐Tuite, Kris Wernstedt, Seth David Guikema · 2025 · International Journal of Disaster Risk Reduction
66. Statistical ranking with dynamic covariates
    Pinjun Dong, Ruijian Han, Binyan Jiang, Yiming Xu · 2025 · Journal of the Royal Statistical Society Series B (Statistical Methodology)
67. Mitigating Low-Level Visual Hallucinations Requires Self-Awareness: Database, Model, and Training Strategy
    Yinan Sun, Xiongkuo Min, Zicheng Zhang, Yixuan Gao, Yuqin Cao, Guangtao Zhai · 2025 · IEEE Transactions on Circuits and Systems for Video Technology
68. Measuring issue salience for political parties using LLMs
    Kenneth R. Benoit, Michael Laver · 2026 · West European Politics
69. Inferring Sparse Preference Lists from Partial Information
    Vivek F. Farias, Srikanth Jagabathula, Devavrat Shah B · 2020 · Stochastic Systems
70. Rank‐based data synthesis of heterogeneous trials to identify the effects of climatic factors on the reaction of Musa genotypes to black leaf streak disease
    David Brown, Sytze de Bruin, Kauê de Sousa, Catherine Abadie, Sébastien Carpentier, Lewis Machida, Jacob van Etten · 2023 · Agronomy Journal
71. Effective signal reconstruction from multiple ranked lists via convex optimization
    Michael G. Schimek, Luca Vitale, Bastian Pfeifer, Michele La Rocca · 2024 · Data Mining and Knowledge Discovery
72. A robust rank aggregation method for malicious disturbance based on objective credit
    Dongmei Chen, Yu Xiao, Huan Zhu, Ye Deng, Jun Ji Wu · 2024 · Applied Soft Computing
73. Bayesian inference for partial orders from random linear extensions: Power relations from 12th century royal acta
    Geoff K. Nicholls, Jeong Eun Lee, Nicholas Karn, David H. Johnson, Rukuang Huang, Alexis Muir Watt · 2025 · The Annals of Applied Statistics
74. A Probabilistic preference learning approach for multiple criteria ranking in dynamic decision context
    Siyuan Zhao, Jiapeng Liu, Miłosz Kadziński, Xiuwu Liao, Yao Wang · 2025 · European Journal of Operational Research
75. Minimax Hypothesis Testing for the Bradley–Terry–Luce Model
    Anuran Makur, Japneet Singh · 2025 · IEEE Transactions on Information Theory
76. A unified analysis of likelihood-based estimators in the Plackett–Luce model
    Ruijian Han, Yiming Xu · 2025 · The Annals of Statistics
77. Multiresolution analysis of incomplete rankings with applications to prediction
    Eric Sibony, Stéphan Clémençon, Jérémie Jakubowicz · 2014 · IEEE International Conference on Big Data (BigData)
78. Revisiting Random Utility Models
    Hossein Azari Soufiani · 2014
79. Application of List-Wise Rank Learning to Property Search for Renovation
    Ping-Chieh Cheng, Kenichiro Kobayashi, Takehiko Hashimoto, Kazunori Saito, Yasufumi Takama · 2017 · Conference on Technologies and Applications of Artificial Intelligence (TAAI)
80. OFAI-UKP at HAHA@IberLEF2019: Predicting the Humorousness of Tweets Using Gaussian Process Preference Learning
    Tristan Miller, Erik-Lân Do Dinh, Edwin Simpson, Iryna Gurevych · 2019 · TUbilio (Technical University of Darmstadt)
81. Ranking Creative Language Characteristics in Small Data Scenarios
    Julia Siekiera, Marius Köppel, Edwin Simpson, Kevin Stowe, Iryna Gurevych, Stefan Krämer · 2020 · TUbilio (Technical University of Darmstadt)
82. Computing Choice: Learning Distributions over Permutations
    Devavrat Shah B · 2021 · Cambridge University Press eBooks
83. Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling
    Jiaqi Ma, Xingjian Zhang, Qiaozhu Mei · 2022 · ACM International Conference on Web Search and Data Mining (WSDM)
84. Dirichlet–Luce choice model for learning from interactions
    Gökhan Çapan, İlker Gündoğdu, Ali Caner Türkmen, Ali Taylan Cemgil · 2022 · User Modeling and User-Adapted Interaction
85. A Robust Bayesian Estimation Approach for the Imprecise Plackett–Luce Model
    Tathagata Basu, Sébastien Destercke, Benjamin Quost · 2022 · Communications in computer and information science
86. Testing for the Bradley-Terry-Luce Model
    Anuran Makur, Japneet Singh · 2023 · IEEE International Symposium on Information Theory (ISIT)
87. Speech Intelligibility versus Congruency: User Preferences of the Acoustics of Virtual Reality Game Spaces
    Constantin Popp, Damian Thomas Murphy · 2024 · Virtual Worlds
88. Dynamic prediction of the National Hockey League draft with rank-ordered logit models
    Brendan Kumagai, Ryker Moreau, Kimberly Kroetch, Tim B. Swartz · 2024 · International Journal of Forecasting
89. Towards Group-aware Search Success
    Haolun Wu, Bhaskar Mitra, Nick Craswell · 2024 · ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR)
90. Item Preference Parameters from Grouped Ranking Observations
    Hideitsu Hino, Yu Fujimoto, Noboru Murata · 2009 · Lecture notes in computer science
91. Credibility as Signal: Predicting Evaluations of Credibility by a Signal-Based Model
    Grzegorz Kowalik, Adam Wierzbicki, Tomasz Borzyszkowski, Wojciech Jaworski · 2016 · IEEE/WIC/ACM International Conference on Web Intelligence
92. Lower Bounds on the Bayes Risk of the Bayesian BTL Model With Applications to Comparison Graphs
    Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan · 2018 · IEEE Journal of Selected Topics in Signal Processing
93. Ranking Median Regression: Learning to Order through Local Consensus
    Stéphan Clémençon, Anna Korba, Eric Sibony · 2017 · HAL
94. Bradley-Terry Modeli ile Türkiye Basketbol Süper Ligi’nde Takımların Ev Sahibi Olma Avantajının İncelenmesi
    Serpil Aktaş, Melike Kaya Bahçecitapar, Rıfat ERGAN · 2018 · Spor Bilimleri Dergisi
95. Sequential decision model for inference and prediction on nonuniform hypergraphs with application to knot matching from computational forestry
    Seong-Hwan Jun, Samuel W. K. Wong, James V. Zidek, Alexandre Bouchard‐Côté · 2019 · The Annals of Applied Statistics
96. On Top-k Selection from m-wise Partial Rankings via Borda Counting
    Wenjing Chen, Ruida Zhou, Chao Tian, Cong Shen · 2020 · IEEE International Symposium on Information Theory (ISIT)
97. Incentives for Item Duplication Under Fair Ranking Policies
    Giorgio Maria Di Nunzio, Alessandro Fabris, Gianmaria Silvello, Gian Antonio Susto · 2021 · Communications in computer and information science
98. MRA-based statistical learning from incomplete rankings
    Eric Sibony, Stéphan Clémençon, Jérémie Jakubowicz · 2015
99. The minimax bookie
    Daniel Barry, John A. Hartigan · 1996 · Journal of Applied Probability
100. Improving pairwise comparison models using Empirical Bayes shrinkage
     Stephen Ragain, Alexander Peysakhovich, Johan H. Ugander · 2018 · arXiv (Cornell University)