brandeis-machine-learning / influence-fairness
Code for ICML 2022 paper: Achieving Fairness at No Utility Cost via Data Reweighing with Influence
☆11Updated 2 years ago
Alternatives and similar repositories for influence-fairness:
Users that are interested in influence-fairness are comparing it to the libraries listed below
- ☆17Updated 3 years ago
- Official implementation of “Code Recommendation for Open Source Software Developers" at The Web Conference 2023 (WWW 2023).☆16Updated last year
- ☆39Updated last year
- ☆26Updated 2 years ago
- Models, data, and codes for the paper: MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models☆18Updated 3 months ago
- Graph Injection Adversarial Attack & Defense Dataset , extracted from KDD CUP 2020 ML2 Track☆21Updated 5 months ago
- SCR: Training Graph Neural Networks with Consistency Regularization☆37Updated 2 years ago
- The dataset for paper "Why Do We Click: Visual Impression-aware News Recommendation", ACM MM 2021☆14Updated 2 years ago
- KDD 2022 Invariant Preference Learning for General Debiasing in Recommendation☆21Updated 2 years ago
- A unified framework for recommender system attacking☆28Updated 9 months ago
- [ACL 2023 Findings] What In-Context Learning “Learns” In-Context: Disentangling Task Recognition and Task Learning☆22Updated last year
- Official codes of paper "Deep causal reasoning for recommendations (Deep-Deconf)". (TIST'23)☆26Updated last year
- [ICLR 2022] Understanding and Improving Graph Injection Attack by Promoting Unnoticeability☆37Updated last year
- ☆61Updated last year
- This is the official implementation of the paper "Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Lea…☆12Updated last month
- [WSDM 2024 best paper honorable mention] Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Expos…☆11Updated 7 months ago
- [KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks☆29Updated 3 years ago
- Official Implementation of Information Theoretic Counterfactual Learning from Missing Not At Random Feedback. NeurIPS 2020.☆28Updated 3 years ago
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆26Updated 2 years ago
- Official implementation of Privacy Implications of Retrieval-Based Language Models (EMNLP 2023). https://arxiv.org/abs/2305.14888☆35Updated 7 months ago
- The source code for BatchSampler that accepted in KDD'23☆18Updated last year
- AutoLossGen: Automatic Loss Function Generation for Recommender Systems☆22Updated 2 years ago
- Group-conditional DRO to alleviate spurious correlations☆15Updated 3 years ago
- [ICML 2021] Information Obfuscation of Graph Neural Networks☆36Updated 3 years ago
- The code and data of SIGIR21 paper "Package Recommendation with Intra- and Inter-Package Attention Networks".☆12Updated 3 years ago
- Tutorial by Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia and Felice Antonio Merra about Adversarial Machine Learning in Recommende…☆25Updated 3 years ago
- The Implementation of "AutoNE: Hyperparameter Optimization for Massive Network Embedding"(KDD 2019)☆17Updated last year
- Implementation of meta-tail2vec published in CIKM 2020 paper "Towards Locality-Aware Meta-Learning of Tail Node Embeddings on Networks".☆13Updated 4 years ago
- Open-source code for ''Individual Fairness for Graph Neural Networks: A Ranking based Approach''.☆12Updated 2 years ago
- The code for "Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation"☆42Updated last year