Cover Image

LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kochar, Dimple Vijay, Wang, Hanrui, Chandrakasan, Anantha, Zhang, Xin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can an Actor-Critic Optimization Framework Improve Analog Design Optimization?
by: Dutta, Sounak, et al.
Published: (2026)

Bayesian Learning of Optimal Policies in Markov Decision Processes with Countably Infinite State-Space
by: Adler, Saghar, et al.
Published: (2023)

Advanced AI Service Provisioning in O-RAN through LLM Engine Integration
by: Natanzi, Seyed Bagher Hashemi, et al.
Published: (2026)

Harnessing Data from Clustered LQR Systems: Personalized and Collaborative Policy Optimization
by: Kanakeri, Vinay, et al.
Published: (2025)

EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization
by: Song, Zhiye, et al.
Published: (2026)

Enhancing Functional Safety in Automotive AMS Circuits through Unsupervised Machine Learning
by: Arunachalam, Ayush, et al.
Published: (2024)

A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints
by: Wang, Lei, et al.
Published: (2022)

Combined Peak Reduction and Self-Consumption Using Proximal Policy Optimization
by: Peirelinck, Thijs, et al.
Published: (2022)

Compression Method for Deep Diagonal State Space Model Based on $H^2$ Optimal Reduction
by: Sakamoto, Hiroki, et al.
Published: (2025)

MuaLLM: A Multimodal Large Language Model Agent for Circuit Design Assistance with Hybrid Contextual Retrieval-Augmented Generation
by: Abbineni, Pravallika, et al.
Published: (2025)

Quantitative Error Feedback for Quantization Noise Reduction of Filtering over Graphs
by: Zheng, Xue Xian, et al.
Published: (2025)

Model-Free Learning for the Linear Quadratic Regulator over Rate-Limited Channels
by: Ye, Lintao, et al.
Published: (2024)

Few-shot Learning on AMS Circuits and Its Application to Parasitic Capacitance Prediction
by: Shen, Shan, et al.
Published: (2025)

Learning to Admit Optimally in an $M/M/k/k+N$ Queueing System with Unknown Service Rate
by: Adler, Saghar, et al.
Published: (2022)

Personalized Collaborative Learning with Affinity-Based Variance Reduction
by: Zhang, Chenyu, et al.
Published: (2025)

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning
by: Li, Jiayu, et al.
Published: (2025)

Investigating the Impact of Observation Space Design Choices On Training Reinforcement Learning Solutions for Spacecraft Problems
by: Hamilton, Nathaniel, et al.
Published: (2025)

Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
by: Ye, Lintao, et al.
Published: (2022)

End-to-End Learning Framework for Solving Non-Markovian Optimal Control
by: Zhang, Xiaole, et al.
Published: (2025)

A SISA-based Machine Unlearning Framework for Power Transformer Inter-Turn Short-Circuit Fault Localization
by: Liu, Nanhong, et al.
Published: (2026)

HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecasting
by: Song, Pengyang, et al.
Published: (2025)

Process, Bias and Temperature Scalable CMOS Analog Computing Circuits for Machine Learning
by: Kumar, Pratik, et al.
Published: (2022)

Communication-aware Wide-Area Damping Control using Risk-Constrained Reinforcement Learning
by: Kwon, Kyung-bin, et al.
Published: (2025)

Gradient Estimation and Variance Reduction in Stochastic and Deterministic Models
by: Keane, Ronan
Published: (2024)

GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments
by: Orfanoudakis, Stavros, et al.
Published: (2025)

Enhancing Field-Oriented Control of Electric Drives with Tiny Neural Network Optimized for Micro-controllers
by: Elele, Martin Joel Mouk, et al.
Published: (2025)

Transferable Parasitic Estimation via Graph Contrastive Learning and Label Rebalancing in AMS Circuits
by: Shen, Shan, et al.
Published: (2025)

Domain Adaptation of Drag Reduction Policy to Partial Measurements
by: Plaksin, Anton, et al.
Published: (2025)

Space-Filling Regularization for Robust and Interpretable Nonlinear State Space Models
by: Klein, Hermann, et al.
Published: (2025)

Accelerating Optimization and Machine Learning through Decentralization
by: Chen, Ziqin, et al.
Published: (2026)

Learning Stable and Robust Linear Parameter-Varying State-Space Models
by: Verhoek, Chris, et al.
Published: (2023)

Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems
by: Zhang, Hanli, et al.
Published: (2024)

RadioDiff-Loc: Diffusion Model Enhanced Scattering Congnition for NLoS Localization with Sparse Radio Map Estimation
by: Wang, Xiucheng, et al.
Published: (2025)

Proximal Reliability Optimization for Reinforcement Learning
by: Patwardhan, Narendra, et al.
Published: (2019)

Local Updates in Distributed Optimization: Provable Acceleration and Topology Effects
by: Wang, Zuang, et al.
Published: (2026)

Learning-Enhanced Safeguard Control for High-Relative-Degree Systems: Robust Optimization under Disturbances and Faults
by: Wang, Xinyang, et al.
Published: (2025)

Online Regularized Statistical Learning in Reproducing Kernel Hilbert Space With Non-Stationary Data
by: Zhang, Xiwei, et al.
Published: (2024)

Parametric Nonconvex Optimization via Convex Surrogates
by: Wang, Renzi, et al.
Published: (2026)

Cluster-Based Multi-Agent Task Scheduling for Space-Air-Ground Integrated Networks
by: Wang, Zhiying, et al.
Published: (2024)

Data Driven Automatic Electrical Machine Preliminary Design with Artificial Intelligence Expert Guidance
by: Wang, Yiwei, et al.
Published: (2024)