:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autor principal:	Tomar, Yash Vardhan
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2506.23033
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

DiffFP: Learning Behaviors from Scratch via Diffusion-based Fictitious Play
por: Karthikeyan, Akash, et al.
Publicado: (2025)

GenPlan: Generative Sequence Models as Adaptive Planners
por: Karthikeyan, Akash, et al.
Publicado: (2024)

Enhancing Safety in Mixed Traffic: Learning-Based Modeling and Efficient Control of Autonomous and Human-Driven Vehicles
por: Wang, Jie, et al.
Publicado: (2024)

Adaptformer: Sequence models as adaptive iterative planners
por: Karthikeyan, Akash, et al.
Publicado: (2024)

Mitigating Gender Bias in Contextual Word Embeddings
por: Yarrabelly, Navya, et al.
Publicado: (2024)

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability
por: Aggarwal, Yash, et al.
Publicado: (2026)

Impact of Label Noise on Learning Complex Features
por: Vashisht, Rahul, et al.
Publicado: (2024)

Meta-Continual Mobility Forecasting for Proactive Handover Prediction
por: Mandapati, Sasi Vardhan Reddy
Publicado: (2025)

Metric-DST: Mitigating Selection Bias Through Diversity-Guided Semi-Supervised Metric Learning
por: Tepeli, Yasin I., et al.
Publicado: (2024)

CG-CNN: Self-Supervised Feature Extraction Through Contextual Guidance and Transfer Learning
por: Kursun, Olcay, et al.
Publicado: (2021)

Controllable Feature Whitening for Hyperparameter-Free Bias Mitigation
por: Cho, Yooshin, et al.
Publicado: (2025)

Mixed Blessing: Class-Wise Embedding guided Instance-Dependent Partial Label Learning
por: Yang, Fuchao, et al.
Publicado: (2024)

Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data
por: Baligodugula, Vishnu Vardhan, et al.
Publicado: (2025)

Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning
por: Thellier, Elie, et al.
Publicado: (2025)

Learning and Generalization with Mixture Data
por: Vardhan, Harsh, et al.
Publicado: (2025)

Directional Neural Collapse Explains Few-Shot Transfer in Self-Supervised Learning
por: Luthra, Achleshwar, et al.
Publicado: (2026)

SetAD: Semi-Supervised Anomaly Learning in Contextual Sets
por: Gao, Jianling, et al.
Publicado: (2025)

Post-hoc Orthogonalization for Mitigation of Protected Feature Bias in CXR Embeddings
por: Weber, Tobias, et al.
Publicado: (2023)

Interpretable Predictive Models for Healthcare via Rational Logistic Regression
por: Suttaket, Thiti, et al.
Publicado: (2024)

Corruptions of Supervised Learning Problems: Typology and Mitigations
por: Iacovissi, Laura, et al.
Publicado: (2023)

Leakage-Aware Bandgap Prediction on the JARVIS-DFT Dataset: A Phase-Wise Feature Analysis
por: Sharma, Gaurav Kumar
Publicado: (2025)

Understanding and Mitigating the Bias in Sample Selection for Learning with Noisy Labels
por: Wei, Qi, et al.
Publicado: (2024)

Multi-Scale Harmonic Encoding for Feature-Wise Graph Message Passing
por: Li, Longlong, et al.
Publicado: (2025)

Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
por: Chang, Xiangyu, et al.
Publicado: (2025)

MulTi-Wise Sampling: Trading Uniform T-Wise Feature Interaction Coverage for Smaller Samples
por: Pett, Tobias, et al.
Publicado: (2024)

LoSA: Locality Aware Sparse Attention for Block-Wise Diffusion Language Models
por: Xi, Haocheng, et al.
Publicado: (2026)

Identification and Mitigating Bias in Quantum Machine Learning
por: Swaminathan, Nandhini, et al.
Publicado: (2024)

Counterfactual Reward Model Training for Bias Mitigation in Multimodal Reinforcement Learning
por: Mathew, Sheryl, et al.
Publicado: (2025)

Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems
por: Gao, Jikun, et al.
Publicado: (2024)

Anomaly Detection and Improvement of Clusters using Enhanced K-Means Algorithm
por: Shorewala, Vardhan, et al.
Publicado: (2025)

AICO: Feature Significance Tests for Supervised Learning
por: Giesecke, Kay, et al.
Publicado: (2025)

Contextual Bandits in Payment Processing: Non-uniform Exploration and Supervised Learning
por: Vangara, Akhila, et al.
Publicado: (2024)

Federated Learning Framework via Distributed Mutual Learning
por: Gupta, Yash
Publicado: (2025)

Client Selection in Federated Learning with Data Heterogeneity and Network Latencies
por: Vardhan, Harsh, et al.
Publicado: (2025)

Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
por: Gan, Kai, et al.
Publicado: (2024)

Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
por: Oh, Yongjeong, et al.
Publicado: (2023)

Mixed Supervised Graph Contrastive Learning for Recommendation
por: Zhang, Weizhi, et al.
Publicado: (2024)

Distribution-Free Robust Predict-Then-Optimize in Function Spaces
por: Patel, Yash, et al.
Publicado: (2026)

Mitigating Copy Bias in In-Context Learning through Neuron Pruning
por: Ali, Ameen, et al.
Publicado: (2024)

A Copula Based Supervised Filter for Feature Selection in Diabetes Risk Prediction Using Machine Learning
por: Aich, Agnideep, et al.
Publicado: (2025)