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This is the tenth year of ICTS-TIFR since it came into existence on 2nd August 2007. ICTS has now grown to have more than fifteen faculty in a number of areas in the theoretical sciences. Over 150 programs and discussion meetings have been held. The ICTS at Ten event is an opportunity to reflect on the journey thus far, and to go ahead with renewed energy into our second decade, through a small celebratory scientific gathering.There will be broad perspective talks (of 30 minutes each) across several different themes in the theoretical sciences: Astrophysics and Cosmology String theory and Quantum Gravity Mathematics Theoretical Computer Science Condensed Matter and Statistical Physics Physical BiologyThese reflect ICTS' present profile as well as the directions we would like to grow into in the coming years. The talks, by a galaxy of distinguished researchers, will give a broad perspective on some exciting frontier questions in these areas.  

This is the tenth year of ICTS-TIFR since it came into existence on 2nd August 2007. ICTS has now grown to have more than fifteen faculty in a number of areas in the theoretical sciences. Over 150 programs and discussion meetings have been held. The ICTS at Ten event is an opportunity to reflect on the journey thus far, and to go ahead with renewed energy into our second decade, through a small celebratory scientific gathering.There will be broad perspective talks (of 30 minutes each) across several different themes in the theoretical sciences: Astrophysics and Cosmology String theory and Quantum Gravity Mathematics Theoretical Computer Science Condensed Matter and Statistical Physics Physical BiologyThese reflect ICTS' present profile as well as the directions we would like to grow into in the coming years. The talks, by a galaxy of distinguished researchers, will give a broad perspective on some exciting frontier questions in these areas.  

The goal of this discussion meeting is to bring together leading young researchers in the areas of algorithms and optimization to discuss and disseminate the recent directions and advances in these areas. The topics include learning algorithms, convex optimization, nonconvex optimization, combinatorial optimization, spectral algorithms, semidefinite programming-based algorithms, parallel algorithms, counting algorithms, and their applications. 

The goal of this discussion meeting is to bring together leading young researchers in the areas of algorithms and optimization to discuss and disseminate the recent directions and advances in these areas. The topics include learning algorithms, convex optimization, nonconvex optimization, combinatorial optimization, spectral algorithms, semidefinite programming-based algorithms, parallel algorithms, counting algorithms, and their applications. 

The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the "thermodynamic" limit of large number of variables. Methods from statistical physics (eg various mean-field approaches) simplify the performance analysis of these algorithms in the limit of many variables. In particular, phase-transition like phenomena appear where the performance can undergo a discontinuous change as an underlying parameter is continuously varied. A provocative question to be explored at the meeting is whether these methods can shed theoretical light into the workings of deep networks for machine learning.The Discussion Meeting will aim to facilitate interaction between theoretical computer scientists, statistical physicists, machine learning researchers and mathematicians interested in these questions. Examples of specific topics to be covered include (but are not limited to) problems such as phase transitions in optimiz...

The theme of this Discussion Meeting is the analysis of distributed/networked algorithms in machine learning and theoretical computer science in the "thermodynamic" limit of large number of variables. Methods from statistical physics (eg various mean-field approaches) simplify the performance analysis of these algorithms in the limit of many variables. In particular, phase-transition like phenomena appear where the performance can undergo a discontinuous change as an underlying parameter is continuously varied. A provocative question to be explored at the meeting is whether these methods can shed theoretical light into the workings of deep networks for machine learning.The Discussion Meeting will aim to facilitate interaction between theoretical computer scientists, statistical physicists, machine learning researchers and mathematicians interested in these questions. Examples of specific topics to be covered include (but are not limited to) problems such as phase transitions in optimiz...

Holomorphic curves are a central object of study in complex algebraic geometry. Such curves are meaningful even when the target has an almost complex structure. The moduli space of these curves (called pesudoholomorphic curves) is typically non-compact and not well-behaved. A nice compactification, due to Gromov, allows us to define certain invariants known as Gromov-Witten invariants.The theory of Gromov-Witten invariants can be used to deform the usual cohomology ring structure of a symplectic manifold. This has connections, on the one hand, with enumerative geometry, and on the other hand, with deformation of associative algebras and topological quantum field theory. Gromov-Witten invariants have deep connections with physics through the ideas of Mirror Symmetry. Using String Theory, physicists have made amazing predictions about the Gromov-Witten invariants of the quintic threefold. From a mathematical point of view, a large number of predictions are still open.The study of pseudoh...