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Optimization

1638 directly classified papers

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Papers

PTQ4DiT: Post-training Quantization for Diffusion Transformers NIPS 2024
The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks NIPS 2024
Nature-Inspired Local Propagation NIPS 2024
BOLD: Boolean Logic Deep Learning NIPS 2024
The Fine-Grained Complexity of Gradient Computation for Training Large Language Models NIPS 2024
Understanding and Improving Optimization in Predictive Coding Networks AAAI 2024
Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe NIPS 2024
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models NIPS 2024
Robust and Faster Zeroth-Order Minimax Optimization: Complexity and Applications NIPS 2024
Fast Forwarding Low-Rank Training EMNLP 2024
Scaling Laws in Linear Regression: Compute, Parameters, and Data NIPS 2024
LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication NIPS 2024
QTIP: Quantization with Trellises and Incoherence Processing NIPS 2024
The Price of Implicit Bias in Adversarially Robust Generalization NIPS 2024
Local Curvature Smoothing with Stein's Identity for Efficient Score Matching NIPS 2024
DeltaDEQ: Exploiting Heterogeneous Convergence for Accelerating Deep Equilibrium Iterations NIPS 2024
Worst-Case VCG Redistribution Mechanism Design Based on the Lottery Ticket Hypothesis AAAI 2024
Taming Binarized Neural Networks and Mixed-Integer Programs AAAI 2024
Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization NIPS 2024
Dual Lagrangian Learning for Conic Optimization NIPS 2024
Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations NIPS 2024
Alias-Free Mamba Neural Operator NIPS 2024
HEPrune: Fast Private Training of Deep Neural Networks With Encrypted Data Pruning NIPS 2024
Exploring Token Pruning in Vision State Space Models NIPS 2024
Gradients of Functions of Large Matrices NIPS 2024