Image de couverture de livre

Aggregating Data for Optimal and Private Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Agarwal, Sushant, Makhija, Yukti, Saket, Rishi, Raghuveer, Aravindan
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Weak to Strong Learning from Aggregate Labels
par: Makhija, Yukti, et autres
Publié: (2024)

FRACTAL: Fine-Grained Scoring from Aggregate Text Labels
par: Makhija, Yukti, et autres
Publié: (2024)

Dense and Diverse Goal Coverage in Multi Goal Reinforcement Learning
par: Singh, Sagalpreet, et autres
Publié: (2025)

Algorithmic Guarantees for Distilling Supervised and Offline RL Datasets
par: Gupta, Aaryan, et autres
Publié: (2025)

LLP-Bench: A Large Scale Tabular Benchmark for Learning from Label Proportions
par: Brahmbhatt, Anand, et autres
Publié: (2023)

Learning from Label Proportions and Covariate-shifted Instances
par: Singh, Sagalpreet, et autres
Publié: (2024)

Learning Predictive Checklists with Probabilistic Logic Programming
par: Makhija, Yukti, et autres
Publié: (2024)

Modularity aided consistent attributed graph clustering via coarsening
par: Bhatia, Samarth, et autres
Publié: (2024)

Preserving Expert-Level Privacy in Offline Reinforcement Learning
par: Sharma, Navodita, et autres
Publié: (2024)

Hardness of Learning Boolean Functions from Label Proportions
par: Guruswami, Venkatesan, et autres
Publié: (2024)

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
par: Havaldar, Shreyas, et autres
Publié: (2023)

Fairness under Covariate Shift: Improving Fairness-Accuracy tradeoff with few Unlabeled Test Samples
par: Havaldar, Shreyas, et autres
Publié: (2023)

Location Aware Embedding for Geotargeting in Sponsored Search Advertising
par: Gligorijevic, Jelena, et autres
Publié: (2026)

On the Power of Randomization in Fair Classification and Representation
par: Agarwal, Sushant, et autres
Publié: (2024)

Federated Learning for Estimating Heterogeneous Treatment Effects
par: Makhija, Disha, et autres
Publié: (2024)

Samplable Anonymous Aggregation for Private Federated Data Analysis
par: Talwar, Kunal, et autres
Publié: (2023)

Rate-Optimal Rank Aggregation with Private Pairwise Rankings
par: Xu, Shirong, et autres
Publié: (2024)

Volume Optimality in Conformal Prediction with Structured Prediction Sets
par: Gao, Chao, et autres
Publié: (2025)

Secure Aggregation Meets Sparsification in Decentralized Learning
par: Biswas, Sayan, et autres
Publié: (2024)

Reliable Active Learning from Unreliable Labels via Neural Collapse Geometry
par: Goel, Atharv, et autres
Publié: (2025)

Private Mean Estimation with Person-Level Differential Privacy
par: Agarwal, Sushant, et autres
Publié: (2024)

Agnostic Learning of Arbitrary ReLU Activation under Gaussian Marginals
par: Guo, Anxin, et autres
Publié: (2024)

Crafting Tomorrow: The Influence of Design Choices on Fresh Content in Social Media Recommendation
par: Saket, Srijan, et autres
Publié: (2024)

Beyond Surface-Level Similarity: Hierarchical Contamination Detection for Synthetic Training Data in Foundation Models
par: Mehta, Sushant
Publié: (2025)

Achieving Fairness Across Local and Global Models in Federated Learning
par: Makhija, Disha, et autres
Publié: (2024)

EVaDE : Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning
par: Aravindan, Siddharth, et autres
Publié: (2025)

Graph Reconstruction from Differentially Private GNN Explanations
par: Sahoo, Rishi Raj, et autres
Publié: (2026)

When Are Learning Biases Equivalent? A Unifying Framework for Fairness, Robustness, and Distribution Shift
par: Mehta, Sushant
Publié: (2025)

On Optimal Hyperparameters for Differentially Private Deep Transfer Learning
par: Rehn, Aki, et autres
Publié: (2025)

Aletheia: Gradient-Guided Layer Selection for Efficient LoRA Fine-Tuning Across Architectures
par: Saket, Abdulmalek
Publié: (2026)

PREM: Privately Answering Statistical Queries with Relative Error
par: Ghazi, Badih, et autres
Publié: (2025)

InData: Towards Secure Multi-Step, Tool-Based Data Analysis
par: K, Karthikeyan, et autres
Publié: (2025)

Scalable Permutation-Aware Modeling for Temporal Set Prediction
par: Ranjan, Ashish, et autres
Publié: (2025)

Agnostic Learning of General ReLU Activation Using Gradient Descent
par: Awasthi, Pranjal, et autres
Publié: (2022)

Optimal Locally Private Nonparametric Classification with Public Data
par: Ma, Yuheng, et autres
Publié: (2023)

Towards minimax optimal algorithms for Active Simple Hypothesis Testing
par: Vijayan, Sushant
Publié: (2025)

Perfectly-Private Analog Secure Aggregation in Federated Learning
par: Jaramillo-Velez, Delio, et autres
Publié: (2025)

On Using Secure Aggregation in Differentially Private Federated Learning with Multiple Local Steps
par: Heikkilä, Mikko A.
Publié: (2024)

Secure and Private Federated Learning: Achieving Adversarial Resilience through Robust Aggregation
par: Yang, Kun, et autres
Publié: (2025)

Robust Reward Modeling via Causal Rubrics
par: Srivastava, Pragya, et autres
Publié: (2025)