1st International Conference on Automated Machine Learning
Accepted Papers: Late-Breaking Workshop
Self-Referential Meta Learning Louis Kirsch, Jürgen Schmidhuber PDFVideoTeaser
A Study of Zero-Cost Proxies for Remote Sensing Image Segmentation Chen Wei, Tai Kai Guo, Ping Yi Tang, Yao Jun Ge, Jimin Liang PDFVideoTeaser
HPO: We won’t get fooled again René Traoré, Andrés Camero, Xiao Xiang Zhu PDFVideoTeaser
Automated Architecture Search for Brain-inspired Hyperdimensional Computing Junhuan Yang, Yi Sheng, Sizhe Zhang, Ruixuan Wang, Kenneth Foreman, Mikell Paige, Dayane Reis, Xun Jiao, Weiwen Jiang, Lei Yang PDFVideoTeaser *
Lightweight Neural Architecture Search with Parameter Remapping and Knowledge Distillation Hayeon Lee, Sohyun An, Minseon Kim, Sung Ju Hwang PDFVideoTeaser *
Evolved Optimizer for Vision Xiangning Chen, Chen Liang, Da Huang, Esteban Real, Yao Liu, Kaiyuan Wang, Cho-Jui Hsieh, Yifeng Lu, Quoc V Le PDFVideoTeaser
Speeding up NAS with Adaptive Subset Selection Vishak Prasad C, Colin White, Paarth Jain, Sibasis Nayak, Rishabh K Iyer, Ganesh Ramakrishnan PDFVideoTeaser *
Bayesian AutoML for Databases via the InferenceQL Probabilistic Programming System Ulrich Schaechtle, Cameron Freer, Zane Shelby, Feras Saad, Vikash Mansinghka PDFVideoTeaser
N-1 Experts: Unsupervised Anomaly Detection Model Selection Constantin Le Clei, Yasha Pushak, Fatjon Zogaj, Moein Owhadi Kareshk, Zahra Zohrevand, Robert Harlow, Hesam Fathi Moghadam, Sungpack Hong, Hassan Chafi PDFVideoTeaser
Getting the Best Bang For Your Buck: Choosing What to Evaluate for Faster Bayesian Optimization Md Shahriar Iqbal, Jianhai Su, Lars Kotthoff, Pooyan Jamshidi PDFVideoTeaser *
Simple and Effective Gradient-Based Tuning of Sequence-to-Sequence Models Jared Lichtarge, Chris Alberti, Shankar Kumar PDFVideoTeaser *
Distribution-Based Invariant Deep Networks for Learning Meta-Features Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michele Sebag PDFVideoTeaser
DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture Kaichen Zhou, Lanqing HONG, Shoukang Hu, Fengwei Zhou, Binxin Ru, Jiashi Feng, Zhenguo Li PDFVideoTeaser
Assembled-OpenML: Creating Efficient Benchmarks for Ensembles in AutoML with OpenML Lennart Oswald Purucker, Joeran Beel PDFVideoTeaser *
Improved Max-value Entropy Search for Multi-objective Bayesian Optimization with Constraints Daniel Fernández-Sánchez, Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato PDFVideoTeaser *
Dynamic and Efficient Gray-Box Hyperparameter Optimization for Deep Learning Martin Wistuba, Arlind Kadra, Josif Grabocka PDFVideoTeaser *
LiteTransformerSearch: Training-free On-device Search for Efficient Autoregressive Language Models Mojan Javaheripi, Shital Shah, Subhabrata Mukherjee, Tomasz Lukasz Religa, Caio Cesar Teodoro Mendes, Gustavo Henrique de Rosa, Sebastien Bubeck, Farinaz Koushanfar, Debadeepta Dey PDFVideoTeaser *
On the Generalizability and Predictability of Recommender Systems John P Dickerson, Sujay Khandagale, Duncan C. McElfresh, Jonathan Valverde, Colin White PDFVideoTeaser *
Adaptive Gradient Methods with Local Guarantees Zhou Lu, Wenhan Xia, Sanjeev Arora, Elad Hazan PDFVideo Teaser
Adversarial Projections to Tackle Support-Query Shifts in Few-Shot Meta-Learning Aroof Aimen, Bharat Ladrecha, Narayanan Chatapuram Krishnan PDFVideoTeaser
GSparsity: Unifying Network Pruning and Neural Architecture Search by Group Sparsity Avraam Chatzimichailidis, Arber Zela, Janis Keuper, Yang Yang PDFVideoTeaser
Graph Embedding for Neural Architecture Search with Input-Output Information Gabriela Suchopárová, Roman Neruda PDFVideoTeaser *
How to Learn and Represent Abstractions: An Investigation using Symbolic Alchemy Badr AlKhamissi, Akshay Srinivasan, Zeb Kurth-Nelson, Samuel Ritter PDFVideoTeaser
A Hardware-Aware Framework for Accelerating Neural Architecture Search Across Modalities Daniel Cummings, Anthony Sarah, Sharath Nittur Sridhar, Maciej Szankin, Juan Pablo Munoz, Sairam Sundaresan PDFVideoTeaser *
Searching Efficient Dynamic Graph CNN for Point Cloud Processing Panyue Chen, Rui Wang, Ping Zhao, Guanming Liu, Zhihua Wei PDFVideoTeaser
Regularized Meta-Learning for Neural Architecture Search Rob van Gastel, Joaquin Vanschoren PDFVideoTeaser *
PASHA: Efficient HPO with Progressive Resource Allocation Ondrej Bohdal, Lukas Balles, Beyza Ermis, Cedric Archambeau, Giovanni Zappella PDFVideoTeaser *
Towards Automated Distillation: A Systematic Study of Knowledge Distillation in Natural Language Processing Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis PDFVideoTeaser
ALBench: A Framework for Evaluating Active Learning in Object Detection Zhanpeng Feng, Shiliang Zhang, Rinyoichi Takezoe, Wenze Hu, Manmohan Chandraker, Li-jia Li, Vijay K. Narayanan, Xiaoyu Wang PDFVideoTeaser
