no code implementations • 1 Jun 2023 • Kihyuk Sohn, Albert Shaw, Yuan Hao, Han Zhang, Luisa Polania, Huiwen Chang, Lu Jiang, Irfan Essa
We study domain-adaptive image synthesis, the problem of teaching pretrained image generative models a new style or concept from as few as one image to synthesize novel images, to better understand the compositional image synthesis.
4 code implementations • 2 Jun 2022 • Sehoon Kim, Amir Gholami, Albert Shaw, Nicholas Lee, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Kurt Keutzer
After re-examining the design choices for both the macro and micro-architecture of Conformer, we propose Squeezeformer which consistently outperforms the state-of-the-art ASR models under the same training schemes.
Ranked #30 on Speech Recognition on LibriSpeech test-clean
Automatic Speech Recognition Automatic Speech Recognition (ASR)
1 code implementation • 5 Aug 2019 • Albert Shaw, Daniel Hunter, Forrest Iandola, Sammy Sidhu
For real time applications utilizing Deep Neural Networks (DNNs), it is critical that the models achieve high-accuracy on the target task and low-latency inference on the target computing platform.
Ranked #63 on Semantic Segmentation on Cityscapes val (using extra training data)
1 code implementation • NeurIPS 2019 • Albert Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai
Neural Architecture Search (NAS) has been quite successful in constructing state-of-the-art models on a variety of tasks.
no code implementations • ICLR 2018 • Bo Dai, Albert Shaw, Niao He, Lihong Li, Le Song
This paper proposes a new actor-critic-style algorithm called Dual Actor-Critic or Dual-AC.
no code implementations • ICML 2018 • Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song
When function approximation is used, solving the Bellman optimality equation with stability guarantees has remained a major open problem in reinforcement learning for decades.