Copertina

VTruST: Controllable value function based subset selection for Data-Centric Trustworthy AI

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Das, Soumi, Nag, Shubhadip, Sharma, Shreyyash, Bhattacharya, Suparna, Bhattacharya, Sourangshu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

A Data-Driven Defense against Edge-case Model Poisoning Attacks on Federated Learning
di: Purohit, Kiran, et al.
Pubblicazione: (2023)

Sample Efficient Demonstration Selection for In-Context Learning
di: Purohit, Kiran, et al.
Pubblicazione: (2025)

A Greedy Hierarchical Approach to Whole-Network Filter-Pruning in CNNs
di: Purohit, Kiran, et al.
Pubblicazione: (2024)

EXPLORA: Efficient Exemplar Subset Selection for Complex Reasoning
di: Purohit, Kiran, et al.
Pubblicazione: (2024)

SafeTail: Efficient Tail Latency Optimization in Edge Service Scheduling via Computational Redundancy Management
di: Shokhanda, Jyoti, et al.
Pubblicazione: (2024)

The Bayesian Reflex: Online Learning as the Autonomic Nervous System of Modern and Future AI
di: Bhattacharya, Durba, et al.
Pubblicazione: (2026)

On Higher-Order Geometric Refinements of Classical Covariance Asymptotics: An Approach via Intrinsic and Extrinsic Information Geometry
di: Amir, Malik, et al.
Pubblicazione: (2026)

A Lightweight Transformer with Phase-Only Cross-Attention for Illumination-Invariant Biometric Authentication
di: Sharma, Arun K., et al.
Pubblicazione: (2024)

Data Efficient Evaluation of Large Language Models and Text-to-Image Models via Adaptive Sampling
di: Xu, Cong, et al.
Pubblicazione: (2024)

CaTE Data Curation for Trustworthy AI
di: Clemens-Sewall, Mary Versa, et al.
Pubblicazione: (2025)

Zero Shot Time Series Forecasting Using Kolmogorov Arnold Networks
di: Bhattacharya, Abhiroop, et al.
Pubblicazione: (2024)

Network Causal Effect Estimation In Graphical Models Of Contagion And Latent Confounding
di: Wu, Yufeng, et al.
Pubblicazione: (2024)

EdgeMask-DG*: Learning Domain-Invariant Graph Structures via Adversarial Edge Masking
di: Bhattacharya, Rishabh, et al.
Pubblicazione: (2026)

Drone Detection and Tracking with YOLO and a Rule-based Method
di: Bhattacharya, Purbaditya, et al.
Pubblicazione: (2025)

Gradient-based Discrete Sampling with Automatic Cyclical Scheduling
di: Pynadath, Patrick, et al.
Pubblicazione: (2024)

Sensor Design for Accuracy-Bounded Estimation via Maximum-Entropy Likelihood Synthesis
di: Bhattacharya, Raktim
Pubblicazione: (2026)

Spatio-temporal DeepKriging in PyTorch: A Supplementary Application to Precipitation Data for Interpolation and Probabilistic Forecasting
di: Nag, Pratik
Pubblicazione: (2025)

Latent Performance Profiling of Large Language Models
di: Chakraborty, Tanmoy, et al.
Pubblicazione: (2026)

Conformal Prediction and Trustworthy AI
di: Bellotti, Anthony, et al.
Pubblicazione: (2025)

Advancing Magnetic Materials Discovery -- A structure-based machine learning approach for magnetic ordering and magnetic moment prediction
di: Verma, Apoorv, et al.
Pubblicazione: (2025)

Recursive Equations For Imputation Of Missing Not At Random Data With Sparse Pattern Support
di: Phung, Trung, et al.
Pubblicazione: (2025)

Factorized Fusion Shrinkage for Dynamic Relational Data
di: Zhao, Peng, et al.
Pubblicazione: (2022)

Causal and Counterfactual Views of Missing Data Models
di: Nabi, Razieh, et al.
Pubblicazione: (2022)

Adaptive parameter-efficient fine-tuning via Hessian-informed subset selection
di: Xu, Shiyun, et al.
Pubblicazione: (2025)

DataMaster: Data-Centric Autonomous AI Research
di: Du, Yaxin, et al.
Pubblicazione: (2026)

FedDPC : Handling Data Heterogeneity and Partial Client Participation in Federated Learning
di: Sen, Mrinmay, et al.
Pubblicazione: (2025)

Response to Discussions of "Causal and Counterfactual Views of Missing Data Models"
di: Nabi, Razieh, et al.
Pubblicazione: (2025)

Proximal Causal Inference With Text Data
di: Chen, Jacob M., et al.
Pubblicazione: (2024)

Designing a Robust, Bounded, and Smooth Loss Function for Improved Supervised Learning
di: Mahato, Soumi, et al.
Pubblicazione: (2026)

Training-Free Cross-Architecture Merging for Graph Neural Networks
di: Bhattacharya, Rishabh, et al.
Pubblicazione: (2026)

Constrained Reweighting of Distributions: an Optimal Transport Approach
di: Chakraborty, Abhisek, et al.
Pubblicazione: (2023)

Entropy-Guided Sampling of Flat Modes in Discrete Spaces
di: Mohanty, Pinaki, et al.
Pubblicazione: (2025)

Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts
di: Nigam, Shubham Kumar, et al.
Pubblicazione: (2024)

The Geometry of the Set of Equivalent Linear Neural Networks
di: Shewchuk, Jonathan Richard, et al.
Pubblicazione: (2024)

PARAMANU-GANITA: Can Small Math Language Models Rival with Large Language Models on Mathematical Reasoning?
di: Niyogi, Mitodru, et al.
Pubblicazione: (2024)

BhashaSetu: Cross-Lingual Knowledge Transfer from High-Resource to Extreme Low-Resource Languages
di: Maji, Subhadip, et al.
Pubblicazione: (2026)

Data-Centric AI in the Age of Large Language Models
di: Xu, Xinyi, et al.
Pubblicazione: (2024)

Late Fusion Multi-task Learning for Semiparametric Inference with Nuisance Parameters
di: Bhattacharya, Sohom, et al.
Pubblicazione: (2025)

Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks
di: Jantre, Sanket, et al.
Pubblicazione: (2023)

Anomaly Resilient Temporal QoS Prediction using Hypergraph Convoluted Transformer Network
di: Kumar, Suraj, et al.
Pubblicazione: (2024)