How do you predict the travel time distribution of a user while factoring in the effect of a traffic disruption on a nearby road? How do you keep track of users’ locations at scale and identify those with similar travel patterns? These are just two of the many research questions that Professor Cong Gao of
What can real-world graphs tell us? This is an area that Assistant Professor Bryan Hooi from the National University of Singapore is delving into as he researches methods for graph-based learning. Graphs are a way of representing objects and the relationships between them, and they are ubiquitous in many areas – from representing relationships and
Companies hire large teams of data scientists to manually tune hyperparameter configurations of deep learning models. These parameters are used to control the learning process and the tuning is extremely tedious and time consuming since it involves training the model to know the resulting performance of each configuration. For Bryan Low, an associate professor at
How can a financial fraud detection model trained in one country be applied in another? How does mastery of C++ lead to rapid mastery of Java and C#? Associate Professor Sinno Jialin Pan from Nanyang Technological University cited the first as an application of transfer learning, and the second as an analogy to explain how
In economic and game theory, zero-sum games are settings for perfect competition where the gain of one player is exactly equal to the loss of the other. But what happens in environments where many intelligent agents – human or artificial – interact with one other? Do these systems attain a state of equilibrium or do they
Abstract Traditional cloud storage has relied almost exclusively on large storage providers, who act as trusted third parties to transfer and store data. This model poses a number of issues including data availability, high operational cost, and data security. In this paper, we introduce a system that leverages blockchain technology to provide a secure distributed
Below are 4 interesting papers from Lee Hwee Kuan’s team over at A*STAR BII on cancer detection using advanced analytics/AI techniques. 1) Nuclear Pleomorphism in Renal Clear Cell Cancer The characteristics of the nuclei are often observed by pathologists when they assess the progression and presence of cancer cells in tissue biopsies. Cancerous tissue typically
Natural language is ambiguous. Human beings can easily disambiguate the meaning of linguistic units such as words, phrases and sentences as they read or listen. However it is difficult for machines to do the same without explicit representations of syntax, semantic and discourse. As a researcher in Natural Language Processing (NLP) at NTU, Professor Joty
Natural language processing (NLP) has been around for more than 50 years but has become more well-known recently, thanks to personal assistant applications such as Apple’s Siri and Amazon’s Alexa. It is also the driving force behind language translation applications such as Google Translate. It has been no easy feat coming this far. Enabling computers
Researchers in natural language processing (NLP) have made significant progress recently. We have also witnessed more NLP applications in widespread use, such as chatbots, grammar checkers and more. One emerging application is medical text mining, which involves the use of NLP algorithms to process clinical notes written by doctors, to derive useful information and knowledge.
