batch size

GR-Gauge: Cost-efficient Training Configuration By Gauging the Gradient Redundancy CVPR 2026 Auto-reconfiguration for Latency Minimization in CPU-based DNN Serving ICML 2025 Batch List-Decodable Linear Regression via Higher Moments ICML 2025 Breaking the Memory Barrier of Contrastive Loss via Tile-Based Strategy CVPR 2025 Exploring smaller batch sizes for a high-performing BabyLM model architecture EMNLP 2025 Faster Convergence of Riemannian Stochastic Gradient Descent with Increasing Batch Size ACML 2025 Haste Makes Waste: A Simple Approach for Scaling Graph Neural Networks ICML 2025 Increasing Batch Size Improves Convergence of Stochastic Gradient Descent with Momentum ACML 2025 ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference ICML 2025 Training with Fewer Bits: Unlocking Edge LLMs Training with Stochastic Rounding EMNLP 2025 Understanding Nonlinear Implicit Bias via Region Counts in Input Space ICML 2025 Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs ICLR 2025 Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning ICML 2024 EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence ICML 2024 Exact Mean Square Linear Stability Analysis for SGD COLT 2024 How Do Large Language Models Acquire Factual Knowledge During Pretraining? NeurIPS 2024 How Two-Layer Neural Networks Learn, One (Giant) Step at a Time JMLR 2024 KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache ICML 2024 Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers NeurIPS 2024 Online Learning and Information Exponents: The Importance of Batch size & Time/Complexity Tradeoffs ICML 2024 On the Effect of Batch Size in Byzantine-Robust Distributed Learning ICLR 2024 Resolving Discrepancies in Compute-Optimal Scaling of Language Models NeurIPS 2024 Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to K-Level Stochastic Optimizations ICML 2024 Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation ICML 2024 A new characterization of the edge of stability based on a sharpness measure aware of batch gradient distribution ICLR 2023