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Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound [article]

Claudio Ferrari, Mark Niklas Muller, Nikola Jovanovic, Martin Vechev
2022 arXiv   pre-print
The latter enables complete verification but becomes increasingly ineffective on larger and more challenging networks.  ...  State-of-the-art neural network verifiers are fundamentally based on one of two paradigms: either encoding the whole verification problem via tight multi-neuron convex relaxations or applying a Branch-and-Bound  ...  Fast and complete: Enabling complete neural network verification with rapid and massively parallel incomplete verifiers. In Proc. of ICLR, 2021.  ... 
arXiv:2205.00263v1 fatcat:q4s6qggpwrdh3at4kjmo47rn74

All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda [article]

Lik-Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang, Dianlei Xu, Zijun Lin, Abhishek Kumar, Carlos Bermejo, Pan Hui
2021 arXiv   pre-print
and Cloud computing, and Future Mobile Networks.  ...  We have created various computer-mediated virtual environments including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokemon Go), and Non-Fungible  ...  However, the verification process for encrypted data is not as fast as conventional approaches.  ... 
arXiv:2110.05352v3 fatcat:pv4fxf5lfbc7vk3ogsyidwfloy

Limits to parallel computation: P-completeness theory

1996 ChoiceReviews  
P -complete problems are of interest because they all appear to lack highly parallel solutions.  ...  Consequently, the promise of parallel computation, namely that applying more processors to a problem can greatly speed its solution, appears to be broken by the entire class of P -complete problems.  ...  He shows a deterministic recurrent neural network that has at least one stable state can learn any P -complete language; he gives conditions restricting the thresholds and weights that result in neural  ... 
doi:10.5860/choice.33-3959 fatcat:qjoueeu225gr7jvwdf6gkoxfbq

Protein crystallization: virtual screening and optimization

L DELUCAS, D HAMRICK, L COSENZA, L NAGY, D MCCOMBS, T BRAY, A CHAIT, B STOOPS, A BELGOVSKIY, W WILLIAMWILSON
2005 Progress in Biophysics and Molecular Biology  
DeLucas). combination of a balanced incomplete factorial screen and neural network analysis may provide an efficient method for producing diffraction-quality protein crystals. r  ...  The screen conditions and scored experimental results are subsequently analyzed using a neural network algorithm to predict new conditions likely to yield improved crystals.  ...  Acknowledgements Funding for this research was provided by the NIH Protein Structure Initiative Grant P50-GM62407 and the NASA Cooperative Agreement NCC 8-246.  ... 
doi:10.1016/j.pbiomolbio.2004.07.008 pmid:15652246 fatcat:r2yx2wf3nbavtc36pm3jmpp3xi

To Root Artificial Intelligence Deeply in Basic Science for a New Generation of AI [article]

Jingan Yang, Yang Peng
2020 arXiv   pre-print
), develop a new inference engine for cognitive network recognition~(CNR); (v)~to develop high-precision, multi-modal intelligent perceptrons; (vi)~investigating intelligent reasoning and fast decision-making  ...  What is the coordination mechanism between brain neural electrical signals and human activities?  ...  When the enthusiasm for Acknowledgments We thank Feng Wu of Changzhou Institute of Technology for assistance with coding and AILab at Stanford University for experimental and technical support.  ... 
arXiv:2009.05678v1 fatcat:vn4pdl3k7jdwrmx4dygsyyfxvy

Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151) [article]

Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak (+6 others)
2017 arXiv   pre-print
surmountable in the short and medium term.  ...  The mission of this workshop was to identify and explore some of the most important research directions that have high relevance to society and to Computer Science today, and where the PDM community has  ...  ., on the Web), and to verify them. Verification of massive data analysis might involve code verification and/or systematic testing.  ... 
arXiv:1701.09007v1 fatcat:cr76noeh4nazlbxuvo7cqrusre

Rigorous Neural Network Simulations: A Model Substantiation Methodology for Increasing the Correctness of Simulation Results in the Absence of Experimental Validation Data

Guido Trensch, Robin Gutzen, Inga Blundell, Michael Denker, Abigail Morrison
2018 Frontiers in Neuroinformatics  
In this manuscript, we propose a terminology for model verification and validation in the field of neural network modeling and simulation.  ...  In order to build credibility, methods such as verification and validation have been developed, but they are not yet well-established in the field of neural network modeling and simulation, partly due  ...  ACKNOWLEDGMENTS We are greatful to Dimitri Plotnikov, Sandra Diaz, Alexander Peyser, Jochen Martin Eppler, Sonja Grün, Michael von Papen, Pietro Quaglio, Robin Pauli, and Philipp Weidel for the fruitful  ... 
doi:10.3389/fninf.2018.00081 pmid:30534066 pmcid:PMC6275234 fatcat:opbj4ttnwzgvloydauhkgsqx5i

Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges [article]

Triet H. M. Le, Hao Chen, M. Ali Babar
2020 arXiv   pre-print
Then, we present the state-of-the-art practices and discuss their challenges with some recommendations for practitioners and researchers as well.  ...  Deep Learning (DL) techniques for Natural Language Processing have been evolving remarkably fast.  ...  Thus, alternative architectures for rapid, parallel sample generation are required. Gu et al.  ... 
arXiv:2002.05442v1 fatcat:bt7dtzrcnjfk5jn6kmin2ruqii

Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2015 Budget Estimates

Department Of Defense Comptroller's Office
2014 Zenodo  
The budget request details the proposed investments $80 million to develop new sets of tools for imaging and analytics of neural and synaptic brain activities that will improve diagnosis and care of wounded  ...  Included in this category is the National Center for Advancing Translational Sciences (NCATS) efforts to reengineer drug discovery and development in collaboration with industry, academia, the Food and  ...  -Investigate design evaluation tools to enable massively parallel testing, validation, and verification of engineered systems.  ... 
doi:10.5281/zenodo.1215345 fatcat:fjzhmynqjbaafk67q2ckcblj2m

A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions [article]

Pengzhen Ren, Yun Xiao, Xiaojun Chang, Po-Yao Huang, Zhihui Li, Xiaojiang Chen, Xin Wang
2021 arXiv   pre-print
Neural Architecture Search (NAS) is just such a revolutionary algorithm, and the related research work is complicated and rich.  ...  However, the design of the neural architecture heavily relies on the researchers' prior knowledge and experience.  ...  Fast Neural Network Adaptation (FNA) [60] proposes a method that can adapt a network's architecture and parameters to new tasks at almost zero cost.  ... 
arXiv:2006.02903v3 fatcat:u3k66cclarcbjd7dhkh5rdb6cu

Defense Advanced Research Projects Agency (Darpa) Fiscal Year 2016 Budget Estimates

Department Of Defense Comptroller's Office
2015 Zenodo  
-Investigate design evaluation tools to enable massively parallel testing, validation, and verification of engineered systems.  ...  -Complete verified 2D and 3D bonded composite pi-joint structure models.  ... 
doi:10.5281/zenodo.1215366 fatcat:cqn5tyfixjanzp5x3tgfkpedri

Deep reinforcement learning based mobile robot navigation: A review

Kai Zhu, Tao Zhang
2021 Tsinghua Science and Technology  
Then we systematically compare and analyze the relationship and differences between four typical application scenarios: local obstacle avoidance, indoor navigation, multi-robot navigation, and social navigation  ...  In this paper, we review DRL methods and DRL-based navigation frameworks.  ...  Its powerful representation ability enabled another breakthrough for RL by its integration with deep neural networks to constitute DRL.  ... 
doi:10.26599/tst.2021.9010012 fatcat:7rrkw43mqffdjnmgvxkxjwrhkm

Deep Learning in Mobile and Wireless Networking: A Survey [article]

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 arXiv   pre-print
The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure.  ...  We first briefly introduce essential background and state-of-the-art in deep learning techniques with potential applications to networking.  ...  Serving Deep Learning with Massive High-Quality Data Deep neural networks rely on massive and high-quality data to achieve good performance.  ... 
arXiv:1803.04311v3 fatcat:awuvyviarvbr5kd5ilqndpfsde

Deep Learning in Mobile and Wireless Networking: A Survey

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 IEEE Communications Surveys and Tutorials  
The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure.  ...  We first briefly introduce essential background and state-of-theart in deep learning techniques with potential applications to networking.  ...  Serving Deep Learning with Massive High-Quality Data Deep neural networks rely on massive and high-quality data to achieve good performance.  ... 
doi:10.1109/comst.2019.2904897 fatcat:xmmrndjbsfdetpa5ef5e3v4xda

Digital twin: a state-of-the-art review of its enabling technologies, applications and challenges

Weifei Hu, Tongzhou Zhang, Xiaoyu Deng, Zhenyu Liu, Jianrong Tan
2021 Journal of Intelligent Manufacturing and Special Equipment  
Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies.  ...  Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas.  ...  (SVR), gradient boosting regressor (GBR) and artificial neural network (ANN) (Zaccaria et al., 2018; Balakrishnan, 2019) .  ... 
doi:10.1108/jimse-12-2020-010 fatcat:4py4isl5czgwrkhdfwf3r3uj4a
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