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20172021
most citedTowards Automated Neural Interaction Discovery for Click-Through Rate Prediction

64 citations · 211 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CV2020

FBNetV3: Joint Architecture-Recipe Search using Predictor Pretraining

Xiaoliang Dai, Alvin Wan, Peizhao Zhang +8

Neural Architecture Search (NAS) yields state-of-the-art neural networks that outperform their best manually-designed counterparts. However, previous NAS methods search for archite…

cs.CV2020★ 29 cited

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

Alvin Wan, Xiaoliang Dai, Peizhao Zhang +9

Differentiable Neural Architecture Search (DNAS) has demonstrated great success in designing state-of-the-art, efficient neural networks. However, DARTS-based DNAS's search space i…

cs.CV2019

Bayesian Relational Memory for Semantic Visual Navigation

Yi Wu, Yuxin Wu, Aviv Tamar +3

We introduce a new memory architecture, Bayesian Relational Memory (BRM), to improve the generalization ability for semantic visual navigation agents in unseen environments, where…

cs.CV2018

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

Bichen Wu, Xiaoliang Dai, Peizhao Zhang +7

Designing accurate and efficient ConvNets for mobile devices is challenging because the design space is combinatorially large. Due to this, previous neural architecture search (NAS…

cs.CV2018

Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search

Bichen Wu, Yanghan Wang, Peizhao Zhang +3

Recent work in network quantization has substantially reduced the time and space complexity of neural network inference, enabling their deployment on embedded and mobile devices wi…

cs.CV2018

3D Interpreter Networks for Viewer-Centered Wireframe Modeling

Jiajun Wu, Tianfan Xue, Joseph J. Lim +4

Understanding 3D object structure from a single image is an important but challenging task in computer vision, mostly due to the lack of 3D object annotations to real images. Previ…