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Discretization-Aware Architecture Search [article]

Yunjie Tian, Chang Liu, Lingxi Xie, Jianbin Jiao, Qixiang Ye
2020 arXiv   pre-print
This paper presents discretization-aware architecture search (DA2S), with the core idea being adding a loss term to push the super-network towards the configuration of desired topology, so that the accuracy  ...  The search cost of neural architecture search (NAS) has been largely reduced by weight-sharing methods.  ...  To alleviate the above issue, we propose discretization-aware architecture search (DA 2 S).  ... 
arXiv:2007.03154v1 fatcat:ggaf7owxnjamxioxldv23bldqa

DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation [article]

Yufan He, Dong Yang, Holger Roth, Can Zhao, Daguang Xu
2021 arXiv   pre-print
Recently, neural architecture search (NAS) has been applied to automatically search high-performance networks for medical image segmentation.  ...  The discretization of the searched optimal continuous model in differentiable scheme may produce a sub-optimal final discrete model (discretization gap).  ...  guaranteed discretization algorithm and a discretization aware topology loss for the search stage to minimize the discretization gap. • We develop a memory usage aware search method which is able to search  ... 
arXiv:2103.15954v1 fatcat:a77g2iy6s5gftmgmz5dqzfn26e

NADS: Neural Architecture Distribution Search for Uncertainty Awareness [article]

Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
2020 arXiv   pre-print
NADS searches for a distribution of architectures that perform well on a given task, allowing us to identify common building blocks among all uncertainty-aware architectures.  ...  To address these problems, we first seek to identify guiding principles for designing uncertainty-aware architectures, by proposing Neural Architecture Distribution Search (NADS).  ...  Specifically, let A denote our discrete architecture search space and α ∈ A be an architecture in this space.  ... 
arXiv:2006.06646v1 fatcat:bqzwefudvvezjndhntvgzbs6lq

Pareto-Frontier-aware Neural Architecture Generation for Diverse Budgets [article]

Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan
2021 arXiv   pre-print
To this end, we propose a Pareto-Frontier-aware Neural Architecture Generator (NAG) which takes an arbitrary budget as input and produces the Pareto optimal architecture for the target budget.  ...  Existing methods often perform an independent architecture search for each target budget, which is very inefficient yet unnecessary.  ...  To achieve this, we evenly sample a set of discrete budgets from the range of possible values and maximize the expected reward of the searched architectures over these budgets to approximate the Pareto  ... 
arXiv:2103.00219v1 fatcat:mjrlpdvgnnhurb3rhehcdefyru

Power-aware multimedia: concepts and design perspectives

Chung-Jr Lian, Shao-Yi Chien, Chia-Ping Lin, Po-Chih Tseng, Liang-Gee Chen
2007 IEEE Circuits and Systems Magazine  
It is a hybrid coding architecture based on Discrete Cosine Transform (DCT) and Motion Estimation/ Motion Compensation (ME/MC).  ...  Design perspectives and examples on power aware Motion Estimation (ME) and Discrete Cosine Transform (DCT) will be discussed in this paper followed by discussions and conclusions.  ... 
doi:10.1109/mcas.2007.4299440 fatcat:jaftd26bizdzdai2sjz6kljdfa

Dynamic Routing Networks [article]

Shaofeng Cai, Yao Shu, Wei Wang, Beng Chin Ooi
2020 arXiv   pre-print
Extensive efforts have been made to improve the accuracy with expert-designed or algorithm-searched architectures.  ...  Therefore, customizing the model capacity in an instance-aware manner is much needed for higher inference efficiency.  ...  Neural Architecture Search. There has been an increasing interest in automated architecture search (NAS).  ... 
arXiv:1905.04849v5 fatcat:wmvllbypgvdbzgm3itypu3uhdq

Neighborhood-Aware Neural Architecture Search [article]

Xiaofang Wang, Shengcao Cao, Mengtian Li, Kris M. Kitani
2021 arXiv   pre-print
Based on our formulation, we propose neighborhood-aware random search (NA-RS) and neighborhood-aware differentiable architecture search (NA-DARTS).  ...  Existing neural architecture search (NAS) methods often return an architecture with good search performance but generalizes poorly to the test setting.  ...  NEIGHBORHOOD-AWARE SEARCH ALGORITHMS We propose neighborhood-aware random search and neighborhood-aware DARTS by applying our formulation to random search (sampling-based) and DARTS (gradient-based), respectively  ... 
arXiv:2105.06369v2 fatcat:xiuzkml7rnbzjm3t5xywcgrotu

AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search [article]

Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou
2021 arXiv   pre-print
We incorporate a task-oriented knowledge distillation loss to provide search hints and an efficiency-aware loss as search constraints, which enables a good trade-off between efficiency and effectiveness  ...  Motivated by the necessity and benefits of task-oriented BERT compression, we propose a novel compression method, AdaBERT, that leverages differentiable Neural Architecture Search to automatically compress  ...  Here we solve this problem by modeling searched architecture {K, o i,j } as discrete variables that obey discrete probability distributions P K = [θ K 1 , . . . , θ K Kmax ] and P o = [θ o 1 , . . . ,  ... 
arXiv:2001.04246v2 fatcat:hma3lfdrqnf77axtib26qxafpq

Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation [article]

Dewen Zeng, Weiwen Jiang, Tianchen Wang, Xiaowei Xu, Haiyun Yuan, Meiping Huang, Jian Zhuang, Jingtong Hu, Yiyu Shi
2020 arXiv   pre-print
In this work, we present the first hardware-aware multi-scale neural architecture search (NAS) framework for real-time 3D cardiac cine MRI segmentation.  ...  Experimental results on ACDC MICCAI 2017 dataset demonstrate that our hardware-aware multi-scale NAS framework can reduce the latency by up to 3.5 times and satisfy the real-time constraints, while still  ...  Finally, we will discuss how the network is optimized and how to decode the discrete architecture once the search finishes.  ... 
arXiv:2008.07071v2 fatcat:jpj7ogvtwjb2dirio5v254xa5e

Geometry-Aware Gradient Algorithms for Neural Architecture Search [article]

Liam Li, Mikhail Khodak, Maria-Florina Balcan, Ameet Talwalkar
2021 arXiv   pre-print
Together, our theory and experiments demonstrate a principled way to co-design optimizers and continuous relaxations of discrete NAS search spaces.  ...  Recent state-of-the-art methods for neural architecture search (NAS) exploit gradient-based optimization by relaxing the problem into continuous optimization over architectures and shared-weights, a noisy  ...  to reduce loss from post-search discretization.  ... 
arXiv:2004.07802v5 fatcat:lbmcptmrijbelokdqfv5u2wvky

EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search [article]

Qian Jiang, Xiaofan Zhang, Deming Chen, Minh N. Do, Raymond A. Yeh
2021 arXiv   pre-print
In hardware-aware Differentiable Neural Architecture Search (DNAS), it is challenging to compute gradients of hardware metrics to perform architecture search.  ...  In this work, we propose End-to-end Hardware-aware DNAS (EH-DNAS), a seamless integration of end-to-end hardware benchmarking, and fully automated DNAS to deliver hardware-efficient deep neural networks  ...  Mnasnet: [11] Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Platform-aware neural architecture search for mobile. In Proc.  ... 
arXiv:2111.12299v1 fatcat:hrtt7wr6ifep5nrhlruyeqajre

RC-DARTS: Resource Constrained Differentiable Architecture Search [article]

Xiaojie Jin, Jiang Wang, Joshua Slocum, Ming-Hsuan Yang, Shengyang Dai, Shuicheng Yan, Jiashi Feng
2019 arXiv   pre-print
Recent advances show that Neural Architectural Search (NAS) method is able to find state-of-the-art image classification deep architectures.  ...  In this paper, we propose the resource constrained differentiable architecture search (RC-DARTS) method to learn architectures that are significantly smaller and faster while achieving comparable accuracy  ...  Instead of searching over a discrete set of candidate architectures, they relax the search space to be continuous, so that the architecture can be optimized with respect to its validation set performance  ... 
arXiv:1912.12814v1 fatcat:k2s2lyy7arb4zfxktildn7lssa

MaCAR: Urban Traffic Light Control via Active Multi-agent Communication and Action Rectification

Zhengxu Yu, Shuxian Liang, Long Wei, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Here we solve this problem by modeling searched architecture {K, o i,j } as discrete variables that obey discrete probability distributions P K = [θ K 1 , . . . , θ K Kmax ] and P o = [θ o 1 , . . . ,  ...  By leveraging Neural Architecture Search, we incorporate two kinds of losses, task-useful knowledge distillation loss and model efficiency-aware loss, such that the task-suitable structures of compressed  ... 
doi:10.24963/ijcai.2020/341 dblp:conf/ijcai/ChenLQWLDDHLZ20 fatcat:6rgljj7ab5bzxnca7n7bgqec4a

SHADHO: Massively Scalable Hardware-Aware Distributed Hyperparameter Optimization [article]

Jeff Kinnison, Nathaniel Kremer-Herman, Douglas Thain, Walter Scheirer
2018 arXiv   pre-print
In this paper, we introduce a framework for massively Scalable Hardware-Aware Distributed Hyperparameter Optimization (SHADHO).  ...  Existing hyperparameter optimization methods are highly parallel but make no effort to balance the search across heterogeneous hardware or to prioritize searching high-impact spaces.  ...  architecture search.  ... 
arXiv:1707.01428v2 fatcat:tyxbvw2vs5hplk722kya7p65za

16th International Conference on Computer Communications and Networks (ICCCN2007)

2008 IEICE Communications Society Magazine  
Honiden, Ringed filters for peer-topeer keyword searching, WA4-5.Protection Mechanisms for Well-Behaved TCP Flows from Tampered-TCP at Edge Routers [1] Network-Aware State Update For Large Scale Mobile  ...  Xu, Network-aware state update for large scale mobile games, TP9-3. 1 Signal processing for communications 2 Computer architecture for networking and com- munications 3 Wireless ad-hoc and sensor  ... 
doi:10.1587/bplus.2008.4_56 fatcat:j2q3ylivoffyjbgvtbr4dmy2mi
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