:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Tyagi, Sahil, Wang, Feiyi
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2603.18112
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On Using Large-Batches in Federated Learning
by: Tyagi, Sahil
Published: (2025)

OmniFed: A Modular Framework for Configurable Federated Learning from Edge to HPC
by: Tyagi, Sahil, et al.
Published: (2025)

Piper: Efficient Large-Scale MoE Training via Resource Modeling and Pipelined Hybrid Parallelism
by: Dash, Sajal, et al.
Published: (2026)

Revisiting LARS for Large Batch Training Generalization of Neural Networks
by: Do, Khoi, et al.
Published: (2023)

Reasoning Stabilization Point: A Training-Time Signal for Stable Evidence and Shortcut Reliance
by: Dhayalkar, Sahil Rajesh
Published: (2026)

Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2025)

Towards Optimizing the Costs of LLM Usage
by: Shekhar, Shivanshu, et al.
Published: (2024)

RACE Attention: A Strictly Linear-Time Attention Layer for Training on Outrageously Large Contexts
by: Joshi, Sahil, et al.
Published: (2025)

Robust Batch-Level Query Routing for Large Language Models under Cost and Capacity Constraints
by: Markovic-Voronov, Jelena, et al.
Published: (2026)

Accelerating Large-Scale Dataset Distillation via Exploration-Exploitation Optimization
by: Alahmadi, Muhammad J., et al.
Published: (2026)

Trust the Batch, On- or Off-Policy: Adaptive Policy Optimization for RL Post-Training
by: Fakoor, Rasool, et al.
Published: (2026)

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
by: Lee, Deokjae, et al.
Published: (2024)

GraVAC: Adaptive Compression for Communication-Efficient Distributed DL Training
by: Tyagi, Sahil, et al.
Published: (2023)

Beyond the Mean: Fisher-Orthogonal Projection for Natural Gradient Descent in Large Batch Training
by: Lu, Yishun, et al.
Published: (2025)

A Combinatorial Theory of Dropout: Subnetworks, Graph Geometry, and Generalization
by: Dhayalkar, Sahil Rajesh
Published: (2025)

Building Expressive and Tractable Probabilistic Generative Models: A Review
by: Sidheekh, Sahil, et al.
Published: (2024)

Adaptive Batch-Wise Sample Scheduling for Direct Preference Optimization
by: Huang, Zixuan, et al.
Published: (2025)

A Decomposable Forward Process in Diffusion Models for Time-Series Forecasting
by: Caldas, Francisco, et al.
Published: (2026)

Scaling Up Data Parallelism in Decentralized Deep Learning
by: Xie, Bing, et al.
Published: (2025)

Efficient GNN Training Through Structure-Aware Randomized Mini-Batching
by: Balaji, Vignesh, et al.
Published: (2025)

Time Transfer: On Optimal Learning Rate and Batch Size In The Infinite Data Limit
by: Filatov, Oleg, et al.
Published: (2024)

Batch Acquisition Function Evaluations and Decouple Optimizer Updates for Faster Bayesian Optimization
by: Irie, Kaichi, et al.
Published: (2025)

Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization
by: Ahmadianshalchi, Alaleh, et al.
Published: (2024)

Edge Intelligence Optimization for Large Language Model Inference with Batching and Quantization
by: Zhang, Xinyuan, et al.
Published: (2024)

BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching
by: Zheng, Zhen, et al.
Published: (2024)

Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2023)

Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
by: Ansari, Navid, et al.
Published: (2023)

Accelerating Distributed ML Training via Selective Synchronization
by: Tyagi, Sahil, et al.
Published: (2023)

Self-Certifying Primal-Dual Optimization Proxies for Large-Scale Batch Economic Dispatch
by: Klamkin, Michael, et al.
Published: (2025)

From Theory to Throughput: CUDA-Optimized APML for Large-Batch 3D Learning
by: Sharifipour, Sasan, et al.
Published: (2025)

Test-Time Training on Graphs with Large Language Models (LLMs)
by: Zhang, Jiaxin, et al.
Published: (2024)

Amortized Latent Steering: Low-Cost Alternative to Test-Time Optimization
by: Egbuna, Nathan, et al.
Published: (2025)

Batch Bayesian Active Learning with Partial Batch Label Sampling
by: Hu, Kangping, et al.
Published: (2025)

Generative AI in Ship Design
by: Thakur, Sahil, et al.
Published: (2024)

Federated Instrumental Variable Analysis via Federated Generalized Method of Moments
by: Geetika, et al.
Published: (2025)

Attention as Binding: A Vector-Symbolic Perspective on Transformer Reasoning
by: Dhayalkar, Sahil Rajesh
Published: (2025)

Dynamic Context Adaptation and Information Flow Control in Transformers: Introducing the Evaluator Adjuster Unit and Gated Residual Connections
by: Dhayalkar, Sahil Rajesh
Published: (2024)

Extending Test-Time Scaling: A 3D Perspective with Context, Batch, and Turn
by: Yu, Chao, et al.
Published: (2025)

Sample Transform Cost-Based Training-Free Hallucination Detector for Large Language Models
by: Ding, Zeyang, et al.
Published: (2026)

DVPO: Distributional Value Modeling-based Policy Optimization for LLM Post-Training
by: Zhu, Dingwei, et al.
Published: (2025)