83 citations · 101 across the 4 of their papers we have counts for
6 papers
TorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU
Claudio Basile, Michael Voznesensky, Gunhyun Park +50
TorchTPU is an open-source collaboration between Google and Meta that introduces a native and principled PyTorch backend for Google TPUs. It enables seamless out-of-the-box model e…
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization
Zirui Liu, Haifeng Jin, Ting-Hsiang Wang +2
Human-designed data augmentation strategies have been replaced by automatically learned augmentation policy in the past two years. Specifically, recent work has empirically shown t…
AutoRec: An Automated Recommender System
Ting-Hsiang Wang, Qingquan Song, Xiaotian Han +3
Realistic recommender systems are often required to adapt to ever-changing data and tasks or to explore different models systematically. To address the need, we present AutoRec, an…
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning
Yuening Li, Zhengzhang Chen, Daochen Zha +4
Outlier detection is an important data mining task with numerous practical applications such as intrusion detection, credit card fraud detection, and video surveillance. However, g…
Multi-Label Adversarial Perturbations
Qingquan Song, Haifeng Jin, Xiao Huang +1
Adversarial examples are delicately perturbed inputs, which aim to mislead machine learning models towards incorrect outputs. While most of the existing work focuses on generating…
Auto-Keras: An Efficient Neural Architecture Search System
Haifeng Jin, Qingquan Song, Xia Hu
Neural architecture search (NAS) has been proposed to automatically tune deep neural networks, but existing search algorithms, e.g., NASNet, PNAS, usually suffer from expensive com…