Category
Paper
Our paper, “Improving Imprecise Compressive Sensing Models” written by Dongeun, Rafael and Jaesik is accepted at UAI-2016. http://arxiv.org/abs/1502.04538
Our paper, “The Automatic Statistician: A Relational Perspective” written by Yunseong, Anh and Jaesik is accepted at ICML-2016. http://arxiv.org/pdf/1511.08343v2.pdf
Wonjun and Sol-a (our undergraduate interns) make our Baxter robot play the 2048 game successfully by using Deep Learning algorithms (Deep Reinforcement Learning and Neural Network for Image Recognition). Video: https://youtu.be/RXdGeF0Rvjg
A new pragmatic archiving scheme for spatio-temporal sensor data! Paper, A Scalable and Flexible Repository for Big Sensor Data by Dongeun Lee, Prof. Heonshik Shin (Seoul National University) and Jaesik Choi is accepted at IEEE Sensors Journal.
A new way of predicting changes of stock market by reading news articles! Paper, Reading Documents for Bayesian Online Change Point Detection by Taehoon Kim (undergrad) and Jaesik Choi is accepted at 2015 Empirical Methods in Natural Language Processing (EMNLP-15).
A report on machine learning of Prof. Choi is published in the expert report series for Legislative Knowledge Service (NEXT) of National Assembly Library of Korea.
A New Method for Estimating the Partition Function of Exponential Random Graph Models!Paper, A Deterministic Partition Function Approximation for Exponential Random Graph Models by Wen Pu (Linked In), Jaesik Choi, Yunseong Hwang and Eyal Amir (University of Illinois) is accepted at the… Continue Reading →
New Machine Learning Algorithm that Monitors Memory Behaviors for Secure Embedded Systems! Paper, Memory Heat Map: Anomaly Detection in Real-Time Embedded Systems Using Memory Behavior, by Man-Ki Yoon, Sibin Mohan, Jaesik Choi and Lui Sha is accepted Design Automation Conference (DAC 2015)*. This research is… Continue Reading →
New Learning Compressive Sensing models! Paper, Learning Compressive Sensing Models for Big Spatio-Temporal Data by Dongeun Lee and Jaesik Choi is accepted at 2015 SIAM International Conference on Data Mining (SDM 2015). (December 2014)
The first paper (in the literature) on learning parameters in relational continuous probabilistic models! Paper, “Learning Relational Kalman Filtering” by Jaesik Choi, Eyal Amir, Tianfan Xu and Albert Valocchi is accepted at AAAI-2015 Conference. (November 2014)
