It’s your turn to give ideas for events!

We will receive this year’s budget in short time, so we are pondering over the events that can be organized this year. We really welcome CS grads’ input on avenues of spending this year’s budget. It’s your change to give us event ideas and other suggestions about spending the budget!

 

Please email us about your great and fantastic ideas at

csgs-execs AT cs.mcgill.ca

 

Seminar : In silico molecular evolution and Boltzmann sampling: implications in origin of life and molecular design

Thanks to all CSGS grads for great support at our first seminar of this fall.

Seminar by Carlos Oliver

Seminar by Carlos Oliver

 

Speaker: Carlos G. Oliver
Title: In silico molecular evolution and Boltzmann sampling: implications in origin of life and molecular design.

Abstract: RNA is a class of molecules present in all living organisms that counts on two important properties: information storage and catalytic activity. This duality makes RNA an interesting molecule to study as potentially the first molecule to support life, as well as a key component of many cellular processes. One of the most important factors in determining RNA function is the shape, or structure that the molecule adopts. This shape is determined by a specific set of interactions encoded in the RNA sequence that give rise to a 2D and 3D shape.  To this end, RNA structure prediction algorithms have made substantial progress, and serve as a notable example of computer science being applied to answer fundamental biological questions. While the algorithmics of mapping a sequence to a structure are well established, there still remain many questions about how the composition and exploration of sequence space affects this mapping. In this work, we use structure prediction algorithms, combined with Boltzmann sampling, and evolutionary algorithms to study the energy landscapes of RNA populations under various sequence-space constraints. We show that restricting sequence space has a strong influence on the stability of structure-sequence pairs, the emergence of structural complexity, and the evolutionary dynamics of populations. All of these insights can be used to further our understanding of how sequence-structure space affects the diversity of molecules we observe today, as well as provides useful tools for controlling molecular function.

Seminar 7 : Solving the Halting Problem (One Language at a Time)

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Date: April 7
Time: 1:00-2:00pm
Location: McConnell Room 320

Speaker: Rohan Jacob-Rao
Title: Solving the Halting Problem (One Language at a Time)

Abstract: In the CompLogic group, we study the design of programming languages that can enforce safety properties at compile time. In this talk, I will describe a small language in which program termination is enforced by the typechecker. Though it restricts the programs one can write, the technique can be extended to more expressive languages. I will show the steps involved in proving the termination property, from defining a formal semantics to writing a machine-checked proof.

Seminar 6 : The dual view of Markov Processes

Date: March 17, 2016
Time: 1:00-2:00pm
Location: McConnell Room 320

Speaker: Florence Clerc
Title: The dual view of Markov Processes

Abstract:
I will describe how to view a probabilistic transition system as a transformer of functions rather than as a transformer of probability distributions. A Markov process is normally viewed as a Markov kernel i.e. a map from S x Σ → [0,1] where S is a state space and Σ is a σ-algebra on S. These Markov kernels are morphisms in the Kleisli category of the Giry monad. In recent work by Chaput, Danos, Panangaden and Plotkin, Markov processes were reinterpreted as linear maps on the space of positive L1 functions on S. This is analogous to taking the predicate transformer view of Markov processes. A number of dualities and isomorphisms emerge in this picture. Most interestingly conditional expectation can be understood functorially.

Seminar 5 : Time, bounded rationality and representations in reinforcement learning

Date: February 18 (next Thursday)
Time: 1:00-2:00pm
Location: McConnell Room 320
 
Speaker: Pierre-Luc Bacon
Title: Time, bounded rationality and representations in reinforcement learning
 

Abstract:
In this talk, I will tell about some of the research that I’ve been conducting with Prof. Doina Precup over the last couple years.  The main topic will be the problem of “temporal representation learning” in reinforcement learning. Reinforcement learning is an Artificial Intelligence approach to the problem of sequential decision making, in a world full of uncertainty and under limited computational capacity. As for “representation learning”,  it refers to the problem of autonomously finding and  expressing knowledge within a particular reasoning structure while also improving it over time through experience. I will develop  these ideas through the notion of “bounded rationality” and present some recent mathematical tools that we developed to tackle  this problem. In a sense, the title of this talk also reflects my experience through PhD: a journey to improve and refine my own subjective understanding of the world (and of myself) under limited capacity. Just as for our reinforcement learning agents, I had to  embrace the stochasticity of life while leveraging its regularities. I will try to share both sides of the story: how the research results came about, and how I became more of a researcher over time.

Seminar 4 : Code Fragment Summarization

The Computer Science Graduate Society is pleased to present a talk by Annie Ying on February 11, Thursday. To help us know how much food to order, please fill this Google form if you plan to attend: http://goo.gl/forms/HLEmeB3DZR.

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Date: February 11

Time: 1:00-2:00pm

Location: McConnell Room 320

Speaker: Annie Ying

Title: Code Fragment Summarization

Abstract:
Code fragments are an important resource for understanding the Application Programming Interface (API) of software libraries. Many usage scenarios for code fragments require them to be distilled to their essence: for example, when serving as cues to longer documents, for reminding developers of a previously known idiom, or for displaying search results. This dissertation reports on research on shortening, or summarizing, code fragments and makes three main contributions: a set of lessons learned from a case study on a supervised machine learning approach to the generating code fragment summaries; an empirically grounded catalog of source code summarization practices; and the design, implementation and evaluation of a novel optimization-based summarization technique for code fragments.

Afternoon Tea Every Wednesday

We are starting “Afternoon tea” events for graduate students and faculty members.  Every Wednesday from 3-4 pm the lounge will be reserved for us.  CSGS will provide the tea and cookies! We will also buy a new tea boiler for the lounge. (yaaaay!).  Please come with your own mug.  We hope this will be a good way for all of us to connect and to share our research and non-research interests! There will be plenty of chalks available as well (maybe colourful ones too)!

We start this week!