{"total":64,"rows":[{"id":"2109.09831","title":"SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization","created":"2021-09-20","cited_by_count":230,"area":null},{"id":"2301.08727","title":"Neural Architecture Search: Insights from 1000 Papers","created":"2023-01-20","cited_by_count":139,"area":null},{"id":"2109.06716","title":"HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO","created":"2021-09-14","cited_by_count":112,"area":null},{"id":"2104.01177","title":"How Powerful are Performance Predictors in Neural Architecture Search?","created":"2021-04-02","cited_by_count":90,"area":null},{"id":"2203.01665","title":"$\\beta$-DARTS: Beta-Decay Regularization for Differentiable Architecture Search","created":"2022-03-03","cited_by_count":64,"area":null},{"id":"2103.12424","title":"BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search","created":"2021-03-23","cited_by_count":63,"area":null},{"id":"2101.09336","title":"A Comprehensive Survey on Hardware-Aware Neural Architecture Search","created":"2021-01-22","cited_by_count":61,"area":null},{"id":"2207.12560","title":"AMLB: an AutoML Benchmark","created":"2022-07-25","cited_by_count":55,"area":null},{"id":"2106.10784","title":"iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients","created":"2021-06-21","cited_by_count":51,"area":null},{"id":"2210.01628","title":"Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization","created":"2022-10-04","cited_by_count":37,"area":null},{"id":"2201.13396","title":"NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy","created":"2022-01-31","cited_by_count":36,"area":null},{"id":"2301.12844","title":"Are Random Decompositions all we need in High Dimensional Bayesian Optimisation?","created":"2023-01-30","cited_by_count":36,"area":null},{"id":"2110.05668","title":"NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks","created":"2021-10-12","cited_by_count":32,"area":null},{"id":"2109.00817","title":"NASI: Label- and Data-agnostic Neural Architecture Search at Initialization","created":"2021-09-02","cited_by_count":28,"area":null},{"id":"2111.05850","title":"Towards Green Automated Machine Learning: Status Quo and Future Directions","created":"2021-11-10","cited_by_count":25,"area":null},{"id":"2206.09166","title":"NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search","created":"2022-06-18","cited_by_count":25,"area":null},{"id":"2102.08099","title":"EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search","created":"2021-02-16","cited_by_count":24,"area":null},{"id":"2108.12821","title":"Analyzing and Mitigating Interference in Neural Architecture Search","created":"2021-08-29","cited_by_count":20,"area":null},{"id":"2111.03602","title":"NAS-Bench-x11 and the Power of Learning Curves","created":"2021-11-05","cited_by_count":20,"area":null},{"id":"2103.15798","title":"Rethinking Neural Operations for Diverse Tasks","created":"2021-03-29","cited_by_count":18,"area":null},{"id":"2106.04784","title":"Accelerating Neural Architecture Search via Proxy Data","created":"2021-06-09","cited_by_count":14,"area":null},{"id":"2112.09245","title":"Automated Deep Learning: Neural Architecture Search Is Not the End","created":"2021-12-16","cited_by_count":13,"area":null},{"id":"2210.06015","title":"EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search","created":"2022-10-12","cited_by_count":11,"area":null},{"id":"2403.12821","title":"FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer","created":"2024-03-19","cited_by_count":10,"area":null},{"id":"2405.10299","title":"HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models","created":"2024-05-16","cited_by_count":10,"area":null},{"id":"2106.06799","title":"Zero-Cost Operation Scoring in Differentiable Architecture Search","created":"2021-06-12","cited_by_count":9,"area":null},{"id":"2108.06156","title":"EEEA-Net: An Early Exit Evolutionary Neural Architecture Search","created":"2021-08-13","cited_by_count":9,"area":null},{"id":"2110.10165","title":"NAS-HPO-Bench-II: A Benchmark Dataset on Joint Optimization of Convolutional Neural Network Architecture and Training Hyperparameters","created":"2021-10-19","cited_by_count":9,"area":null},{"id":"2102.06599","title":"Neural Architecture Search as Program Transformation Exploration","created":"2021-02-12","cited_by_count":8,"area":null},{"id":"2104.05309","title":"Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search","created":"2021-04-12","cited_by_count":8,"area":null},{"id":"2102.11382","title":"Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity","created":"2021-02-22","cited_by_count":7,"area":null},{"id":"2301.06393","title":"$\\beta$-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture Search","created":"2023-01-16","cited_by_count":7,"area":null},{"id":"2210.07271","title":"BLOX: Macro Neural Architecture Search Benchmark and Algorithms","created":"2022-10-13","cited_by_count":6,"area":null},{"id":"2302.14772","title":"PA&DA: Jointly Sampling PAth and DAta for Consistent NAS","created":"2023-02-28","cited_by_count":6,"area":null},{"id":"2102.10557","title":"Contrastive Self-supervised Neural Architecture Search","created":"2021-02-21","cited_by_count":5,"area":null},{"id":"2111.13204","title":"BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule","created":"2021-11-25","cited_by_count":5,"area":null},{"id":"2207.07868","title":"CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAS","created":"2022-07-16","cited_by_count":5,"area":null},{"id":"2107.03719","title":"Bag of Tricks for Neural Architecture Search","created":"2021-07-08","cited_by_count":4,"area":null},{"id":"2111.01584","title":"Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems","created":"2021-11-02","cited_by_count":4,"area":null},{"id":"2310.00077","title":"Optimizing with Low Budgets: a Comparison on the Black-box Optimization Benchmarking Suite and OpenAI Gym","created":"2023-09-29","cited_by_count":4,"area":null},{"id":"2201.04194","title":"Neural Capacitance: A New Perspective of Neural Network Selection via Edge Dynamics","created":"2022-01-11","cited_by_count":3,"area":null},{"id":"2303.16938","title":"Are Neural Architecture Search Benchmarks Well Designed? A Deeper Look Into Operation Importance","created":"2023-03-29","cited_by_count":3,"area":null},{"id":"2505.12523","title":"Energy-Aware Deep Learning on Resource-Constrained Hardware","created":"2025-05-18","cited_by_count":3,"area":null},{"id":"2110.01154","title":"An Analysis of Super-Net Heuristics in Weight-Sharing NAS","created":"2021-10-04","cited_by_count":2,"area":null},{"id":"2110.12197","title":"Towards a Robust Differentiable Architecture Search under Label Noise","created":"2021-10-23","cited_by_count":2,"area":null},{"id":"2111.03524","title":"A Data-driven Approach to Neural Architecture Search Initialization","created":"2021-11-05","cited_by_count":2,"area":null},{"id":"2210.14016","title":"Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search","created":"2022-10-25","cited_by_count":2,"area":null},{"id":"2305.04502","title":"MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization","created":"2023-05-08","cited_by_count":2,"area":null},{"id":"2306.06852","title":"Rethink DARTS Search Space and Renovate a New Benchmark","created":"2023-06-12","cited_by_count":2,"area":null},{"id":"2306.06858","title":"Robustifying DARTS by Eliminating Information Bypass Leakage via Explicit Sparse Regularization","created":"2023-06-12","cited_by_count":2,"area":null},{"id":"2607.06839","title":"LEMUR 2: Unlocking Neural Network Diversity for AI","created":"2026-07-07","cited_by_count":2,"area":null},{"id":"2101.04028","title":"Unchain the Search Space with Hierarchical Differentiable Architecture Search","created":"2021-01-11","cited_by_count":1,"area":null},{"id":"2207.12547","title":"The BUTTER Zone: An Empirical Study of Training Dynamics in Fully Connected Neural Networks","created":"2022-07-25","cited_by_count":1,"area":null},{"id":"2209.06626","title":"NAAP-440 Dataset and Baseline for Neural Architecture Accuracy Prediction","created":"2022-09-14","cited_by_count":1,"area":null},{"id":"2103.11820","title":"GPNAS: A Neural Network Architecture Search Framework Based on Graphical Predictor","created":"2021-03-19","cited_by_count":0,"area":null},{"id":"2106.11542","title":"Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis","created":"2021-06-22","cited_by_count":0,"area":null},{"id":"2108.09996","title":"MS-DARTS: Mean-Shift Based Differentiable Architecture Search","created":"2021-08-23","cited_by_count":0,"area":null},{"id":"2109.13466","title":"Delve into the Performance Degradation of Differentiable Architecture Search","created":"2021-09-28","cited_by_count":0,"area":null},{"id":"2112.13023","title":"DARTS without a Validation Set: Optimizing the Marginal Likelihood","created":"2021-12-24","cited_by_count":0,"area":null},{"id":"2211.12419","title":"Accuracy Prediction for NAS Acceleration using Feature Selection and Extrapolation","created":"2022-11-22","cited_by_count":0,"area":null},{"id":"2312.09588","title":"NeuroFlow: Development of lightweight and efficient model integration scheduling strategy for autonomous driving system","created":"2023-12-15","cited_by_count":0,"area":null},{"id":"2312.16046","title":"AdaNAS: Adaptively Post-processing with Self-supervised Neural Architecture Search for Ensemble Rainfall Forecasts","created":"2023-12-26","cited_by_count":0,"area":null},{"id":"2604.24492","title":"Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI","created":"2026-04-27","cited_by_count":0,"area":null},{"id":"2609.35707","title":"ScAn-Bench: Evaluating Scaling Analysis Methodology","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}