Login 
Wednesday, April 4, 2018
Public Access


Category:
Category: All

04
April 2018
Mon Tue Wed Thu Fri Sat Sun
            1
2 3 4 5 6 7 8
9 10 11 12 13 14 15
16 17 18 19 20 21 22
23 24 25 26 27 28 29
30            
8:00am  
9:00am  
10:00am  
11:00am  
12:00pm  
1:00pm  
2:00pm  
3:00pm  
4:00pm [4:00pm]Mathematics Colloquium
Description:
Mathematics Colloquium Date & Time: 4th April, 2018 at 4pm Venue: Ramanujan Hall Speaker: Manoj Gopalkrishnan Title: Imagining how a cell thinks: The design of reaction network schemes that do machine learning Abstract: A living cell responds in sophisticated ways to its environment. Such behavior is all the more remarkable when one considers that a cell is a bag of molecules. A detailed algorithmic explanation is required for how a network of chemical reactions can produce sophisticated behavior. Several previous works have shown that reaction networks are computationally universal and can, in principle, implement any algorithm. The problem is that these constructions have not mapped well onto biological reality, have made wasteful use of the computational potential of the native dynamics of reaction networks, and have not made any contact with statistical mechanics. We seek to address these problems. We find that the mathematical structure of reaction networks is particularly well suited to implementing modern machine learning algorithms. We describe a new reaction network scheme for solving a large class of statistical problems including the problem of how a cell would infer its environment from receptor-ligand bindings. Specificially we show how reaction networks can implement information projection, and consequently a generalized Expectation-Maximization algorithm, to solve maximum likelihood estimation problems in partially-observed exponential families on categorical data. Our scheme can be thought of as an algorithmic interpretation of E. T. Jaynes's vision of statistical mechanics as statistical inference.

5:00pm