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LOW E-Hwa Sandra
PhD Student
CHENG Nien Yuan
Assistant Professor
99.504 High Performance Computing in Science and Engineering
The High Performance Computing in Science and Engineering course aims to enable students to operate effectively on high performance computers.
Feng Li (Shandong University) – Distributed Intelligence: From An Algorithmic Perspective
Feng Li (Shandong University) – Distributed Intelligence: From An Algorithmic Perspective
Chip-based dispersion compensation for faster fibre internet
SUTD scientists developed a novel CMOS-compatible, slow-light-based transmission grating device for the dispersion compensation of high-speed data, significantly lowering data transmission errors.
Francesco Gelli (PayPal) – Applied Information Retrieval
In this talk we are providing some examples of industry application of Information Retrieval, including open domain IR, conversational and sentence classification.
Casting light on counterfeit products through nano-optical technology
SUTD led research in a 3D printed optical security label with nano-sized features. It taps on ambient light sources and is harder to crack due to its 33100 possible combinations.
Lavanya Marla (University of Illinois at Urbana-Champaign) – Greedy Policies and Penalized Information-Relaxation Bounds for EMS: Allocation and Performance Assessment
Lavanya Marla (University of Illinois at Urbana-Champaign) – Greedy Policies and Penalized Information-Relaxation Bounds for EMS: Allocation and Performance Assessment
Costas Courcoubetis (Chinese University of Hong Kong) – Topics in the Analysis and Optimization of Decentralized Systems
Costas Courcoubetis (Chinese University of Hong Kong) – Topics in the Analysis and Optimization of Decentralized Systems
Bryan Low (AI Singapore) – Learning with Less Data: Automated Machine Learning and Bayesian Optimization
In this talk, I will briefly describe our research efforts on learning with less data and automated machine learning. Then, I will discuss in greater detail on one of such efforts: Bayesian optimization (BO), specifically, in how we have progressed from tackling some of the fundamental challenges/issues in BO to applying BO to more complex blackbox optimisation problems.