17 citations · 59 across the 6 of their papers we have counts for
10 papers
Neighborhood-Aware Neural Architecture Search
Xiaofang Wang, Shengcao Cao, Mengtian Li +1
Existing neural architecture search (NAS) methods often return an architecture with good search performance but generalizes poorly to the test setting. To achieve better generaliza…
Efficient Model Performance Estimation via Feature Histories
Shengcao Cao, Xiaofang Wang, Kris Kitani
An important step in the task of neural network design, such as hyper-parameter optimization (HPO) or neural architecture search (NAS), is the evaluation of a candidate model's per…
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification
Xiaofang Wang, Xuehan Xiong, Maxim Neumann +5
Convolutional operations have two limitations: (1) do not explicitly model where to focus as the same filter is applied to all the positions, and (2) are unsuitable for modeling lo…
Point in, Box out: Beyond Counting Persons in Crowds
Yuting Liu, Miaojing Shi, Qijun Zhao +1
Modern crowd counting methods usually employ deep neural networks (DNN) to estimate crowd counts via density regression. Despite their significant improvements, the regression-base…
Learnable Embedding Space for Efficient Neural Architecture Compression
Shengcao Cao, Xiaofang Wang, Kris M. Kitani
We propose a method to incrementally learn an embedding space over the domain of network architectures, to enable the careful selection of architectures for evaluation during compr…
Developmental Bayesian Optimization of Black-Box with Visual Similarity-Based Transfer Learning
Maxime Petit, Amaury Depierre, Xiaofang Wang +2
We present a developmental framework based on a long-term memory and reasoning mechanisms (Vision Similarity and Bayesian Optimisation). This architecture allows a robot to optimiz…