Zobrazeno 1 - 10
of 162
pro vyhledávání: '"Sarma, Anish A."'
Animals move smoothly and reliably in unpredictable environments. Models of sensorimotor control have assumed that sensory information from the environment leads to actions, which then act back on the environment, creating a single, unidirectional pe
Externí odkaz:
http://arxiv.org/abs/2211.05922
Autor:
Sarma, Anish A., Li, Jing Shuang, Stenberg, Josefin, Card, Gwyneth, Heckscher, Elizabeth S., Kasthuri, Narayanan, Sejnowski, Terrence, Doyle, John C.
Feedback is ubiquitous in both biological and engineered control systems. In biology, in addition to typical feedback between plant and controller, we observe feedback pathways within control systems, which we call internal feedback pathways (IFPs),
Externí odkaz:
http://arxiv.org/abs/2110.05029
Neural architectures in organisms support efficient and robust control that is beyond the capability of engineered architectures. Unraveling the function of such architectures is challenging; their components are highly diverse and heterogeneous in t
Externí odkaz:
http://arxiv.org/abs/2109.11752
Descending predictive feedback (DPF) is an ubiquitous yet unexplained phenomenon in the central nervous system. Motivated by recent observations on motor-related signals in the visual system, we approach this problem from a sensorimotor standpoint an
Externí odkaz:
http://arxiv.org/abs/2103.16812
Autor:
Matni, Nikolai, Sarma, Anish A.
We generalize the system level synthesis framework to systems defined by bounded causal linear operators, and use this parameterization to make connections between robust system level synthesis and classical results from the robust control literature
Externí odkaz:
http://arxiv.org/abs/1909.10092
Many applications rely on Web data and extraction systems to accomplish knowledge-driven tasks. Web information is not curated, so many sources provide inaccurate, or conflicting information. Moreover, extraction systems introduce additional noise to
Externí odkaz:
http://arxiv.org/abs/1503.00306
Autor:
Zelmann, Rina, Paulk, Angelique C., Basu, Ishita, Sarma, Anish, Yousefi, Ali, Crocker, Britni, Eskandar, Emad, Williams, Ziv, Cosgrove, G. Rees, Weisholtz, Daniel S., Dougherty, Darin D., Truccolo, Wilson, Widge, Alik S., Cash, Sydney S.
Publikováno v:
In NeuroImage December 2020 223
In this paper we study the tradeoff between parallelism and communication cost in a map-reduce computation. For any problem that is not "embarrassingly parallel," the finer we partition the work of the reducers so that more parallelism can be extract
Externí odkaz:
http://arxiv.org/abs/1206.4377
A significant amount of recent research work has addressed the problem of solving various data management problems in the cloud. The major algorithmic challenges in map-reduce computations involve balancing a multitude of factors such as the number o
Externí odkaz:
http://arxiv.org/abs/1204.1754
Given a large graph G = (V,E) with millions of nodes and edges, how do we compute its connected components efficiently? Recent work addresses this problem in map-reduce, where a fundamental trade-off exists between the number of map-reduce rounds and
Externí odkaz:
http://arxiv.org/abs/1203.5387