Please note: This seminar will take place in MC 5501 and online.
Mika Göös, Assistant Professor
Theory Group, École polytechnique fédérale de Lausanne
We present a top-down lower-bound method for depth-4 Boolean circuits. In particular, we give a new proof of the well-known result that the parity function requires depth-4 circuits of size exponential in n^{1/3}. Our proof is an application of robust sunflowers and block unpredictability.
Joint with Artur Riazanov, Anastasia Sofronova, and Dmitry Sokolov.
Please note: This master’s thesis presentation will take place in DC 2310 and online.
Gengyi Sun, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Shane McIntosh
Please note: This seminar will take place in DC 1304 and online.
Han Zhao, Assistant Professor
Computer Science, University of Illinois Urbana-Champaign
Amazon Visiting Academic, Amazon AI and Search Science
To mitigate the bias exhibited by machine learning models, fairness criteria can be integrated into the training process to ensure fair treatment across all demographics, but it often comes at the expense of model performance. Understanding such tradeoffs, therefore, underlies the design of optimal and fair algorithms.
Please note: This PhD seminar will take place in DC 2564 and online.
Farshad Kazemi, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Shane McIntosh
Please note: This PhD seminar will take place in DC 2564 and online.
Farshad Kazemi, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Shane McIntosh
Please note: This CrySP Speaker Series on Privacy talk will take place in DC 1302 and online.
Kevin Yeo
Research Engineering Manager, Google
PhD candidate, Columbia University
Private information retrieval (PIR) is a very promising cryptographic tool that enables privacy-preserving data querying that has endless implications to real-world applications. Unfortunately, PIR’s high cost remains a hindrance in widespread adoption.
Please note: This seminar will take place in DC 1304.
Marina Meila
Department of Statistics, University of Washington
Senior Fellow, University of Washington’s eScience Institute
Please note: This seminar will take place in M3 4206 and online.
David Wajc, Senior Lecturer | Assistant Professor, Taub Fellow
The Technion, Israel Institute of Technology
Please note: The PhD seminar will take place in DC 2310 and online.
Dihong Jiang, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Yaoliang Yu, Sun Sun
Please note: This master’s thesis presentation will take place in DC 2310 and online.
Temiloluwa Femi-Gege, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Jian Zhao
Please note: This PhD seminar will take place online.
Shaokai Wang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Bin Ma
Please note: This PhD seminar will take place in DC 2102.
Andrew Na, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Justin Wan
Please note: This seminar will take place in M3 4206 and online.
Harold Nieuwboer, PhD student
Korteweg-de Vries Institute and QuSoft
University of Amsterdam
Please note: This PhD seminar will take place online.
Pablo Millán Arias, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Lila Kari
Please note: This PhD seminar will take place online.
Marvin Pafla, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Kate Larson, Mark Hancock
With the rise of large language models (LLMs) like GPT, the field of eXplainable artificial intelligence (XAI) has exploded and produced a plethora of methods (e.g., saliency-maps) to gain insight into deep neural nets. However, human-participant studies question the efficacy of these methods, particularly when the AI output is wrong.
Please note: This PhD seminar will take place online.
Ryan Hancock, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ali Mashtizadeh
Please note: This PhD defence will take place in DC 2310 and virtually.
Glaucia Melo dos Santos, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Paulo Alencar, Daniel Berry, Donald Cowan
Please note: This PhD seminar will take place in DC 2585 and online.
Ashish Gaurav, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Pascal Poupart
Please note: This workshop will take place in DC 1302 and online.
You are invited to join the Machine Learning Theory Workshop on Monday, November 6, 2023 in DC 1302 and online.
This workshop will bring together researchers with expertise in mathematical foundations of machine learning. The purpose of this event is to foster connections and build a research community among learning theorists from various institutions.
Please note: This master’s thesis presentation will take place in DC 3317 and online.
Logan Mosier, Master’s candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Toshiya Hachisuka
Please note: This half-hour seminar will take place in DC 1304.
Ahmed Alquraan, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Samer Al-Kiswany
Please note: This half-hour seminar will take place in DC 1304.
Emil Tsalapatis, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Ali Mashtizadeh
Please note: This PhD seminar will take place in DC 3102.
Mengxiao (Max) Zhang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Chengnian Sun
The Waterloo Computer Museum is hosting a hardware day at which a number of older computers will be on display and running.
Please note: This seminar will take place in M3 4206 and virtually.
Roei Tell, Assistant Professor
Department of Computer and Mathematical Sciences, University of Toronto
