Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Orhan Ocal"'
Autor:
Amirali Aghazadeh, Hunter Nisonoff, Orhan Ocal, David H. Brookes, Yijie Huang, O. Ozan Koyluoglu, Jennifer Listgarten, Kannan Ramchandran
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Finding a biologically-relevant inductive bias for training DNNs on large fitness landscapes is challenging. Here, the authors propose a method called Epistatic Net that improves DNN prediction accuracy and interpretation speed by integrating the kno
Externí odkaz:
https://doaj.org/article/aaa0481b36da43839b3bcab8d8fbcc3a
Autor:
Yijie Huang, Kannan Ramchandran, Hunter M. Nisonoff, Orhan Ocal, Amirali Aghazadeh, David H. Brookes, O. Ozan Koyluoglu, Jennifer Listgarten
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Nature Communications
Nature Communications
Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitne
Autor:
Stevo Bailey, Kannan Ramchandran, Orhan Ocal, Jaeduk Han, Woorham Bae, Elad Alon, Zhongkai Wang, Angie Wang, Borivoje Nikolic, Paul Rigge
Publikováno v:
IEEE Journal of Solid-State Circuits. 54:1993-2008
A 1.89-GHz bandwidth, 175-kHz resolution spectral analysis system-on-chip (SoC), integrating a subsampling analog-to-digital converter (ADC) frontend with a digital reconstruction backend and implementing a 21 600-point sparse Fourier transform based
Autor:
Amirali Aghazadeh, Hunter Nisonoff, Orhan Ocal, David H. Brookes, Yijie Huang, O. Ozan Koyluoglu, Jennifer Listgarten, Kannan Ramchandran
Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1f6ee849c5231a1373527ca13b3e208b
https://doi.org/10.1101/2020.11.24.396994
https://doi.org/10.1101/2020.11.24.396994
Autor:
Orhan Ocal, Kannan Ramchandran
Publikováno v:
ISIT
Matrix-matrix multiplication and its derivatives are fundamental linear-algebraic primitives at the core of many modern optimization and machine learning algorithms. We design a new and novel framework for speeding up large-scale matrix-matrix multip
Publikováno v:
ISIT
Pseudo-Boolean functions are functions whose input variables are binary and output is in the real numbers. These functions show up in many different applications in computer science, finance and economics to name a few. Pseudo-Boolean functions lend
Publikováno v:
ICASSP
We present a method for converting the voices between a set of speakers. Our method is based on training multiple autoencoder paths, where there is a single speaker-independent encoder and multiple speaker-dependent decoders. The autoencoders are tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::51773e2433a99fc51311bb7f550d7693
http://arxiv.org/abs/1905.03864
http://arxiv.org/abs/1905.03864
Autor:
Stevo Bailey, Angie Wang, Orhan Ocal, Woorham Bae, Elad Alon, Paul Rigge, Borivoje Nikolic, Zhongkai Wang, Kannan Ramchandran, Jaeduk Han
Publikováno v:
ESSCIRC
A 1.89-GHz bandwidth, 175-kHz resolution spectral analysis SoC, integrating a subsampling ADC frontend with a digital reconstruction backend and implementing a 21,600-point FFAST sparse FFT [1] has been generated using the Chisel [2] and BAG [3] fram
Publikováno v:
ISIT
Distributed computing allows for large-scale computation and machine learning tasks by enabling parallel computing at massive scale. A critical challenge to speeding up distributed computing comes from stragglers, a crippling bottleneck to system per
Publikováno v:
ISIT
We introduce a new ensemble of random bipartite graphs, which we term the ‘smearing ensemble’, where each left node is connected to some number of consecutive right nodes. Such graphs arise naturally in recovering sparse wavelet coefficients when