Image de couverture de livre

Improving Routability Prediction via NAS Using a Smooth One-shot Augmented Predictor

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Sridhar, Arjun, Chang, Chen-Chia, Zhang, Junyao, Chen, Yiran
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Delta-NAS: Difference of Architecture Encoding for Predictor-based Evolutionary Neural Architecture Search
par: Sridhar, Arjun, et autres
Publié: (2024)

TraceNAS: Zero-shot LLM Pruning via Gradient Trace Correlation
par: Malettira, Prajna G., et autres
Publié: (2026)

Enhancing Contrastive Link Prediction With Edge Balancing Augmentation
par: Chang, Chen-Hao, et autres
Publié: (2025)

RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network
par: Hou, Yunbo, et autres
Publié: (2024)

EDALearn: A Comprehensive RTL-to-Signoff EDA Benchmark for Democratized and Reproducible ML for EDA Research
par: Pan, Jingyu, et autres
Publié: (2023)

A Lightweight Inception Boosted U-Net Neural Network for Routability Prediction
par: Li, Hailiang, et autres
Publié: (2024)

HyperNAS: Enhancing Architecture Representation for NAS Predictor via Hypernetwork
par: Lv, Jindi, et autres
Publié: (2025)

Improving Latent Generalization Using Test-time Compute
par: Chaudhry, Arslan, et autres
Publié: (2026)

A Survey of Research in Large Language Models for Electronic Design Automation
par: Pan, Jingyu, et autres
Publié: (2025)

Zero-Shot Vehicle Model Recognition via Text-Based Retrieval-Augmented Generation
par: Chang, Wei-Chia, et autres
Publié: (2025)

Temporal Smoothness Regularisers for Neural Link Predictors
par: Dileo, Manuel, et autres
Publié: (2023)

LaMAGIC2: Advanced Circuit Formulations for Language Model-Based Analog Topology Generation
par: Chang, Chen-Chia, et autres
Publié: (2025)

Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS
par: Fu, Hao, et autres
Publié: (2024)

TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
par: Zhang, Huanyu, et autres
Publié: (2024)

Kan Extension Transformers: A Categorical Unification of Attention, Diffusion, and Predict-Detach Self-Conditioning
par: Mahadevan, Sridhar
Publié: (2026)

ZEUS: Accelerating Diffusion Models with Only Second-Order Predictor
par: Wang, Yixiao, et autres
Publié: (2026)

FR-NAS: Forward-and-Reverse Graph Predictor for Efficient Neural Architecture Search
par: Zhang, Haoming, et autres
Publié: (2024)

CROP: Circuit Retrieval and Optimization with Parameter Guidance using LLMs
par: Pan, Jingyu, et autres
Publié: (2025)

Improving Predictive Confidence in Medical Imaging via Online Label Smoothing
par: Choudhury, Kushan, et autres
Publié: (2025)

Temporal Window Smoothing of Exogenous Variables for Improved Time Series Prediction
par: Kamal, Mustafa, et autres
Publié: (2025)

Is Smoothness the Key to Robustness? A Comparison of Attention and Convolution Models Using a Novel Metric
par: Chen, Baiyuan
Publié: (2024)

One-shot Robust Federated Learning of Independent Component Analysis
par: Jin, Dian, et autres
Publié: (2025)

Parametric Feature Transfer: One-shot Federated Learning with Foundation Models
par: Beitollahi, Mahdi, et autres
Publié: (2024)

Inexact Column Generation for Bayesian Network Structure Learning via Difference-of-Submodular Optimization
par: Yang, Yiran, et autres
Publié: (2025)

One-shot World Models Using a Transformer Trained on a Synthetic Prior
par: Ferreira, Fabio, et autres
Publié: (2024)

FlashFPS: Efficient Farthest Point Sampling for Large-Scale Point Clouds via Pruning and Caching
par: Fu, Yuzhe, et autres
Publié: (2026)

Improving Random Forests by Smoothing
par: Liu, Ziyi, et autres
Publié: (2025)

Laplacian Heads Improve Transformers by Smoothing Token Representations
par: Zhang, Yuchong, et autres
Publié: (2026)

One-shot Federated Learning via Synthetic Distiller-Distillate Communication
par: Zhang, Junyuan, et autres
Publié: (2024)

Early Approaches to Adversarial Fine-Tuning for Prompt Injection Defense: A 2022 Study of GPT-3 and Contemporary Models
par: Sandoval, Gustavo, et autres
Publié: (2025)

DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
par: Lee, Vint, et autres
Publié: (2023)

Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning
par: Gai, Jingchu, et autres
Publié: (2025)

LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits
par: Chang, Chen-Chia, et autres
Publié: (2024)

MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing
par: Ma, Haiyue, et autres
Publié: (2025)

Label Smoothing Improves Machine Unlearning
par: Di, Zonglin, et autres
Publié: (2024)

Universal Reinforcement Learning in Coalgebras: Asynchronous Stochastic Computation via Conduction
par: Mahadevan, Sridhar
Publié: (2025)

SmoothGNN: Smoothing-aware GNN for Unsupervised Node Anomaly Detection
par: Dong, Xiangyu, et autres
Publié: (2024)

Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
par: Xin, Yuan, et autres
Publié: (2023)

Certifiably-Robust Federated Adversarial Learning via Randomized Smoothing
par: Chen, Cheng, et autres
Publié: (2021)

BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification
par: Wang, Yi-Siang, et autres
Publié: (2026)