{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/fairness/papers/39","list_of":"/task/fairness","task":"Fairness","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":39,"pages_in_order":57,"rows_per_page":100,"rows":[3801,3900],"of":5676,"counts":{"archive_papers_tagged":5676,"with_a_code_link":1714,"where_syntology_ran_a_sample":404,"not_listed_spam_title":0,"listed":5676,"listed_where_code_ran":404,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":329,"every_run_a_failure_of_syntologys_instrument":75,"listed_with_a_run_with_no_instrument_failure":329,"listed_every_run_a_failure_of_syntologys_instrument":75,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/fairness","prev":"/task/fairness/papers/38","next":"/task/fairness/papers/40","papers":[{"url":null,"slug":"complai-theory-of-a-unified-framework-for","title":"ComplAI: Theory of A Unified Framework for Multi-factor Assessment of Black-Box Supervised Machine Learning Models","date":"2022-12-30","arxiv_id":"2212.14599","repositories_listed":0,"syntology":null},{"url":null,"slug":"detection-of-groups-with-biased","title":"Detection of Groups with Biased Representation in Ranking","date":"2022-12-30","arxiv_id":"2301.00719","repositories_listed":0,"syntology":null},{"url":null,"slug":"cluster-level-group-representativity-fairness","title":"Cluster-level Group Representativity Fairness in $k$-means Clustering","date":"2022-12-29","arxiv_id":"2212.14467","repositories_listed":0,"syntology":null},{"url":null,"slug":"political-representation-bias-in-dbpedia-and","title":"Political representation bias in DBpedia and Wikidata as a challenge for downstream processing","date":"2022-12-29","arxiv_id":"2301.00671","repositories_listed":0,"syntology":null},{"url":null,"slug":"properties-of-group-fairness-metrics-for","title":"Properties of Group Fairness Metrics for Rankings","date":"2022-12-29","arxiv_id":"2212.14351","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-algorithms-for-group-distributionally","title":"Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond","date":"2022-12-28","arxiv_id":"2212.13669","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-deep-reinforcement-learning-for","title":"Hierarchical Deep Reinforcement Learning for Age-of-Information Minimization in IRS-aided and Wireless-powered Wireless Networks","date":"2022-12-27","arxiv_id":"2212.13390","repositories_listed":0,"syntology":null},{"url":null,"slug":"bias-mitigation-framework-for-intersectional","title":"Bias Mitigation Framework for Intersectional Subgroups in Neural Networks","date":"2022-12-26","arxiv_id":"2212.13014","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-study-of-gender-bias-in","title":"A Comprehensive Study of Gender Bias in Chemical Named Entity Recognition Models","date":"2022-12-24","arxiv_id":"2212.12799","repositories_listed":0,"syntology":null},{"url":null,"slug":"recommending-on-graphs-a-comprehensive-review","title":"Recommending on graphs: a comprehensive review from a data perspective","date":"2022-12-23","arxiv_id":"2212.12230","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-methods-for-auc-optimization","title":"Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints","date":"2022-12-23","arxiv_id":"2212.12603","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-learning-with-localized-neighborhood","title":"Graph Learning with Localized Neighborhood Fairness","date":"2022-12-22","arxiv_id":"2212.12040","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-seven-layer-model-for-standardising-ai","title":"A Seven-Layer Model for Standardising AI Fairness Assessment","date":"2022-12-21","arxiv_id":"2212.11207","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatgpt-the-end-of-online-exam-integrity","title":"ChatGPT: The End of Online Exam Integrity?","date":"2022-12-19","arxiv_id":"2212.09292","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantifying-fairness-and-discrimination-in","title":"Quantifying fairness and discrimination in predictive models","date":"2022-12-19","arxiv_id":"2212.09868","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-inexact-augmented-lagrangian","title":"Stochastic Inexact Augmented Lagrangian Method for Nonconvex Expectation Constrained Optimization","date":"2022-12-19","arxiv_id":"2212.09513","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-of-speech-centric-trustworthy","title":"A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness","date":"2022-12-18","arxiv_id":"2212.09006","repositories_listed":0,"syntology":null},{"url":null,"slug":"autoslicer-scalable-automated-data-slicing","title":"AutoSlicer: Scalable Automated Data Slicing for ML Model Analysis","date":"2022-12-18","arxiv_id":"2212.09032","repositories_listed":0,"syntology":null},{"url":null,"slug":"provable-fairness-for-neural-network-models","title":"Provable Fairness for Neural Network Models using Formal Verification","date":"2022-12-16","arxiv_id":"2212.08578","repositories_listed":0,"syntology":null},{"url":null,"slug":"manifestations-of-xenophobia-in-ai-systems","title":"Manifestations of Xenophobia in AI Systems","date":"2022-12-15","arxiv_id":"2212.07877","repositories_listed":0,"syntology":null},{"url":null,"slug":"tensions-between-the-proxies-of-human-values","title":"Tensions Between the Proxies of Human Values in AI","date":"2022-12-14","arxiv_id":"2212.07508","repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-infinitesimal-jackknife-mitigating-the","title":"Fair Infinitesimal Jackknife: Mitigating the Influence of Biased Training Data Points Without Refitting","date":"2022-12-13","arxiv_id":"2212.06803","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairroad-achieving-fairness-for-recommender","title":"FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data","date":"2022-12-13","arxiv_id":"2212.06750","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-free-approach-to-fair-solar-pv","title":"Model-Free Approach to Fair Solar PV Curtailment Using Reinforcement Learning","date":"2022-12-13","arxiv_id":"2212.06542","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-text-based-personality-computing","title":"On Text-based Personality Computing: Challenges and Future Directions","date":"2022-12-13","arxiv_id":"2212.06711","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplicity-bias-leads-to-amplified","title":"Simplicity Bias Leads to Amplified Performance Disparities","date":"2022-12-13","arxiv_id":"2212.06641","repositories_listed":0,"syntology":null},{"url":null,"slug":"regulating-gatekeeper-ai-and-data","title":"Regulating Gatekeeper AI and Data: Transparency, Access, and Fairness under the DMA, the GDPR, and beyond","date":"2022-12-09","arxiv_id":"2212.04997","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-characterization-of-maximum-nash-welfare","title":"A Characterization of Maximum Nash Welfare for Indivisible Goods","date":"2022-12-08","arxiv_id":"2212.04203","repositories_listed":0,"syntology":null},{"url":null,"slug":"going-beyond-xai-a-systematic-survey-for","title":"Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning","date":"2022-12-07","arxiv_id":"2212.03954","repositories_listed":0,"syntology":null},{"url":null,"slug":"pareto-pairwise-ranking-for-fairness","title":"Pareto Pairwise Ranking for Fairness Enhancement of Recommender Systems","date":"2022-12-06","arxiv_id":"2212.10459","repositories_listed":0,"syntology":null},{"url":null,"slug":"breaking-the-spurious-causality-of","title":"Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling","date":"2022-12-05","arxiv_id":"2212.02090","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-ensembling-pre-processing-algorithms-lead","title":"Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness?","date":"2022-12-05","arxiv_id":"2212.02614","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiated-federated-reinforcement","title":"Differentiated Federated Reinforcement Learning Based Traffic Offloading on Space-Air-Ground Integrated Networks","date":"2022-12-05","arxiv_id":"2212.02075","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-evolutionary-clustering-have-theoretical","title":"Can Evolutionary Clustering Have Theoretical Guarantees?","date":"2022-12-04","arxiv_id":"2212.01771","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-in-contextual-resource-allocation","title":"Fairness in Contextual Resource Allocation Systems: Metrics and Incompatibility Results","date":"2022-12-04","arxiv_id":"2212.01725","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-in-multi-agent-planning","title":"Fairness in Multi-Agent Planning","date":"2022-12-01","arxiv_id":"2212.00506","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-antidote-data-to-individual","title":"Learning Antidote Data to Individual Unfairness","date":"2022-11-29","arxiv_id":"2211.15897","repositories_listed":0,"syntology":null},{"url":null,"slug":"malign-overfitting-interpolation-can-provably","title":"Malign Overfitting: Interpolation Can Provably Preclude Invariance","date":"2022-11-28","arxiv_id":"2211.15724","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-data-driven-pricing-scheme-for-optimal","title":"A Data-driven Pricing Scheme for Optimal Routing through Artificial Currencies","date":"2022-11-27","arxiv_id":"2211.14793","repositories_listed":0,"syntology":null},{"url":null,"slug":"uav-assisted-space-air-ground-integrated","title":"UAV-Assisted Space-Air-Ground Integrated Networks: A Technical Review of Recent Learning Algorithms","date":"2022-11-27","arxiv_id":"2211.14931","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-impact-of-racial-distribution-in-training","title":"The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Look","date":"2022-11-26","arxiv_id":"2211.14498","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-moral-and-event-centric-inspection-of","title":"A Moral- and Event- Centric Inspection of Gender Bias in Fairy Tales at A Large Scale","date":"2022-11-25","arxiv_id":"2211.14358","repositories_listed":0,"syntology":null},{"url":"/paper/picking-on-the-same-person-does-algorithmic","slug":"picking-on-the-same-person-does-algorithmic","title":"Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?","date":"2022-11-25","arxiv_id":"2211.13972","repositories_listed":0,"syntology":{"n":2,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/picking-on-the-same-person-does-algorithmic#ran","syntology_url":"https://syntology.ai/paper/2211.13972","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.13972"}},"official":null}},{"url":null,"slug":"the-european-ai-liability-directives-critique","title":"The European AI Liability Directives -- Critique of a Half-Hearted Approach and Lessons for the Future","date":"2022-11-25","arxiv_id":"2211.13960","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-artificial-intelligence-xai-from","title":"Explainable Artificial Intelligence (XAI) from a user perspective- A synthesis of prior literature and problematizing avenues for future research","date":"2022-11-24","arxiv_id":"2211.15343","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-job-intelligent-scheduling-with-cross","title":"Multi-Job Intelligent Scheduling with Cross-Device Federated Learning","date":"2022-11-24","arxiv_id":"2211.13430","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairly-allocating-utility-in-constrained","title":"Fairly Allocating Utility in Constrained Multiwinner Elections","date":"2022-11-23","arxiv_id":"2211.12820","repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-design-of-power-control-and-access","title":"Joint Design of Power Control and Access Point Scheduling for Uplink Cell-Free Massive MIMO Networks","date":"2022-11-23","arxiv_id":"2211.12704","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-complexity-of-finding-a-diverse-and","title":"On the Complexity of Finding a Diverse and Representative Committee using a Monotone, Separable Positional Multiwinner Voting Rule","date":"2022-11-23","arxiv_id":"2211.13217","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-for-traffic-signal-1","title":"Reinforcement learning for traffic signal control in hybrid action space","date":"2022-11-23","arxiv_id":"2211.12956","repositories_listed":0,"syntology":null},{"url":null,"slug":"vertical-federated-learning","title":"Vertical Federated Learning: Concepts, Advances and Challenges","date":"2022-11-23","arxiv_id":"2211.12814","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-reinforcement-learning-approach-to-optimize","title":"A Reinforcement Learning Approach to Optimize Available Network Bandwidth Utilization","date":"2022-11-22","arxiv_id":"2211.11949","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bayesian-causal-inference-approach-for","title":"Causal Fairness Assessment of Treatment Allocation with Electronic Health Records","date":"2022-11-21","arxiv_id":"2211.11183","repositories_listed":0,"syntology":null},{"url":null,"slug":"cultural-re-contextualization-of-fairness","title":"Cultural Re-contextualization of Fairness Research in Language Technologies in India","date":"2022-11-21","arxiv_id":"2211.11206","repositories_listed":0,"syntology":null},{"url":null,"slug":"equality-of-effort-via-algorithmic-recourse","title":"Equality of Effort via Algorithmic Recourse","date":"2022-11-21","arxiv_id":"2211.11892","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-increases-adversarial-vulnerability","title":"Fairness Increases Adversarial Vulnerability","date":"2022-11-21","arxiv_id":"2211.11835","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-knowledge-enhanced-multimodal","title":"A survey on knowledge-enhanced multimodal learning","date":"2022-11-19","arxiv_id":"2211.12328","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-algorithmic-fairness-to-mitigate","title":"On the Alignment of Group Fairness with Attribute Privacy","date":"2022-11-18","arxiv_id":"2211.10209","repositories_listed":0,"syntology":null},{"url":null,"slug":"social-diversity-reduces-the-complexity-and","title":"Social Diversity Reduces the Complexity and Cost of Fostering Fairness","date":"2022-11-18","arxiv_id":"2211.10517","repositories_listed":0,"syntology":null},{"url":null,"slug":"auditing-algorithmic-fairness-in-machine","title":"Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN","date":"2022-11-16","arxiv_id":"2211.08742","repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigating-frequency-bias-in-next-basket","title":"Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders","date":"2022-11-16","arxiv_id":"2211.09072","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-energy-efficiency-and-fairness","title":"On Energy Efficiency and Fairness Maximization in RIS-Assisted MU-MISO mmWave Communications","date":"2022-11-15","arxiv_id":"2211.08224","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-penalization-in-stochastic-multi-armed","title":"On Penalization in Stochastic Multi-armed Bandits","date":"2022-11-15","arxiv_id":"2211.08311","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalar-invariant-networks-with-zero-bias","title":"Scalar Invariant Networks with Zero Bias","date":"2022-11-15","arxiv_id":"2211.08486","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-preserving-fairness-guarantees-in","title":"A Survey on Preserving Fairness Guarantees in Changing Environments","date":"2022-11-14","arxiv_id":"2211.07530","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-performance-and-fairness-metrics-in","title":"Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition","date":"2022-11-14","arxiv_id":"2211.07245","repositories_listed":0,"syntology":null},{"url":null,"slug":"early-diagnosis-of-chronic-obstructive","title":"Early Diagnosis of Chronic Obstructive Pulmonary Disease from Chest X-Rays using Transfer Learning and Fusion Strategies","date":"2022-11-13","arxiv_id":"2211.06925","repositories_listed":0,"syntology":null},{"url":null,"slug":"long-bet-will-lose-demystifying-seemingly","title":"Long bet will lose: demystifying seemingly fair gambling via two-armed Futurity bandit","date":"2022-11-12","arxiv_id":"2212.11766","repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-measuring-and-mitigating","title":"Identifying, measuring, and mitigating individual unfairness for supervised learning models and application to credit risk models","date":"2022-11-11","arxiv_id":"2211.06106","repositories_listed":0,"syntology":null},{"url":null,"slug":"practical-approaches-for-fair-learning-with","title":"Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes","date":"2022-11-11","arxiv_id":"2211.06138","repositories_listed":0,"syntology":null},{"url":null,"slug":"casual-conversations-v2-designing-a-large","title":"Casual Conversations v2: Designing a large consent-driven dataset to measure algorithmic bias and robustness","date":"2022-11-10","arxiv_id":"2211.05809","repositories_listed":0,"syntology":null},{"url":null,"slug":"debiasing-methods-for-fairer-neural-models-in","title":"Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey","date":"2022-11-10","arxiv_id":"2211.05617","repositories_listed":0,"syntology":null},{"url":null,"slug":"discrimination-and-class-imbalance-aware","title":"Discrimination and Class Imbalance Aware Online Naive Bayes","date":"2022-11-09","arxiv_id":"2211.04812","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-fairness-and-environmental","title":"Bridging Fairness and Environmental Sustainability in Natural Language Processing","date":"2022-11-08","arxiv_id":"2211.04256","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-with-stepwise-fairness","title":"Reinforcement Learning with Stepwise Fairness Constraints","date":"2022-11-08","arxiv_id":"2211.03994","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-algorithmic-fairness-in-space-time","title":"Towards Algorithmic Fairness in Space-Time: Filling in Black Holes","date":"2022-11-08","arxiv_id":"2211.04568","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-treatment-adherence-of","title":"Predicting Treatment Adherence of Tuberculosis Patients at Scale","date":"2022-11-05","arxiv_id":"2211.02943","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-aware-regression-robust-to","title":"Fairness-aware Regression Robust to Adversarial Attacks","date":"2022-11-04","arxiv_id":"2211.04449","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-aware-predictive-modeling-for","title":"Uncertainty-aware predictive modeling for fair data-driven decisions","date":"2022-11-04","arxiv_id":"2211.02730","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-querying-for-bias-leak-protected","title":"Can Querying for Bias Leak Protected Attributes? Achieving Privacy With Smooth Sensitivity","date":"2022-11-03","arxiv_id":"2211.02139","repositories_listed":0,"syntology":null},{"url":null,"slug":"client-selection-in-federated-learning","title":"Client Selection in Federated Learning: Principles, Challenges, and Opportunities","date":"2022-11-03","arxiv_id":"2211.01549","repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-and-efficient-distributed-edge-learning","title":"Fair and Efficient Distributed Edge Learning with Hybrid Multipath TCP","date":"2022-11-03","arxiv_id":"2211.09723","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairness-in-federated-learning-via-core","title":"Fairness in Federated Learning via Core-Stability","date":"2022-11-03","arxiv_id":"2211.02091","repositories_listed":0,"syntology":null},{"url":null,"slug":"making-machine-learning-datasets-and-models","title":"Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study","date":"2022-11-03","arxiv_id":"2211.02092","repositories_listed":0,"syntology":null},{"url":null,"slug":"fair-visual-recognition-via-intervention-with","title":"Fair Visual Recognition via Intervention with Proxy Features","date":"2022-11-02","arxiv_id":"2211.01253","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-of-clinical-prediction-models","title":"Stability of clinical prediction models developed using statistical or machine learning methods","date":"2022-11-02","arxiv_id":"2211.01061","repositories_listed":0,"syntology":null},{"url":null,"slug":"collaborative-honeypot-defense-in-uav","title":"Collaborative Honeypot Defense in UAV Networks: A Learning-Based Game Approach","date":"2022-10-29","arxiv_id":"2211.01772","repositories_listed":0,"syntology":null},{"url":null,"slug":"addressing-bias-in-face-detectors-using","title":"Addressing Bias in Face Detectors using Decentralised Data collection with incentives","date":"2022-10-28","arxiv_id":"2210.16024","repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigating-health-disparities-in-ehr-via","title":"Mitigating Health Disparities in EHR via Deconfounder","date":"2022-10-28","arxiv_id":"2210.15901","repositories_listed":0,"syntology":null},{"url":null,"slug":"fairclip-social-bias-elimination-based-on","title":"FairCLIP: Social Bias Elimination based on Attribute Prototype Learning and Representation Neutralization","date":"2022-10-26","arxiv_id":"2210.14562","repositories_listed":0,"syntology":null},{"url":null,"slug":"simultaneous-improvement-of-ml-model-fairness","title":"Simultaneous Improvement of ML Model Fairness and Performance by Identifying Bias in Data","date":"2022-10-24","arxiv_id":"2210.13182","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstract-interpretation-based-feature","title":"Abstract Interpretation-Based Feature Importance for SVMs","date":"2022-10-22","arxiv_id":"2210.12456","repositories_listed":0,"syntology":null},{"url":null,"slug":"trustworthy-human-computation-a-survey","title":"Trustworthy Human Computation: A Survey","date":"2022-10-22","arxiv_id":"2210.12324","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-fair-were-covid-19-restriction-decisions","title":"How fair were COVID-19 restriction decisions? A data-driven investigation of England using the dominance-based rough sets approach","date":"2022-10-21","arxiv_id":"2211.00056","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextual-bandits-with-concave-rewards-and","title":"Contextual bandits with concave rewards, and an application to fair ranking","date":"2022-10-18","arxiv_id":"2210.09957","repositories_listed":0,"syntology":null},{"url":null,"slug":"electricity-grid-tariffs-for-electrification","title":"Electricity grid tariffs for electrification in households: Bridging the gap between cross-subsidies and fairness","date":"2022-10-18","arxiv_id":"2210.09690","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-fair-classification-against-poisoning","title":"Towards Fair Classification against Poisoning Attacks","date":"2022-10-18","arxiv_id":"2210.09503","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-search-explainability-with","title":"Evaluating Search System Explainability with Psychometrics and Crowdsourcing","date":"2022-10-17","arxiv_id":"2210.09430","repositories_listed":0,"syntology":null},{"url":null,"slug":"loss-minimization-through-the-lens-of-outcome","title":"Loss Minimization through the Lens of Outcome Indistinguishability","date":"2022-10-16","arxiv_id":"2210.08649","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-powered-tiebreak-mechanisms-an-application","title":"AI-powered mechanisms as judges: Breaking ties in chess","date":"2022-10-15","arxiv_id":"2210.08289","repositories_listed":0,"syntology":null}],"record_sha256":"a2687e003a5c35dac674c96a1cea9ee5ad3d532d53f41f009b81b4b8c05bd558","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}