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- 2Wen, Junfeng
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Interrelating Prediction and Control Objectives in Episodic Actor-Critic Reinforcement Learning
DownloadFall 2020
The reinforcement learning framework provides a simple way to study computational intelligence as the interaction between an agent and an environment. The goal of an agent is to accrue as much reward as possible by intelligently choosing actions given states. This problem of finding a policy that...
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Spring 2011
Standard survival analysis focuses on population-based studies. The objective of our work, survival prediction, is different: to find the most accurate model for predicting the survival times for each individual patient. We view this as a regression problem, where we try to map the features for...
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Learning Deep Representations, Embeddings and Codes from the Pixel Level of Natural and Medical Images
DownloadFall 2013
Significant research has gone into engineering representations that can identify high-level semantic structure in images, such as objects, people, events and scenes. Recently there has been a shift towards learning representations of images either on top of dense features or directly from the...
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Spring 2020
In the field of metabolomics, mass spectrometry (MS) is the most widely adopted method for identifying metabolites. Conventionally, metabolite identification involves matching the target mass spectrum against experimentally acquired reference mass spectral libraries. However, the limited coverage...
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Fall 2023
Of all the capabilities of natural intelligence, one of the most exceptional is the ability to expand upon and refine knowledge of the world through subjective experience. Therefore, a longstanding goal of Artificial Intelligence has been to replicate this success: to enable artificial agents to...
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Spring 2023
With machine learning models becoming more complicated and more widely applied to solve real-world challenges, there comes the need to explain their reasoning. In parallel with the advancements of deep learning methods, Explainable AI (XAI) algorithms have been proposed to address the issue of...
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Machine learning for medical applications with limited data: Incorporating domain expertise and addressing domain-shift
DownloadFall 2022
Machine learning has the potential to help medical experts to deliver better healthcare. There are, however, important technical challenges that need to be solved before we can develop reliable models for clinical practice, including: (1) Limited number of labeled instances, (2) Uncertainty of...
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Fall 2021
The optimization of non-convex objective functions is a topic of central interest in machine learning. Remarkably, it has recently been shown that simple gradient-based optimization can achieve globally optimal solutions in important non-convex problems that arise in machine learning, including...
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Spring 2021
It has gotten increasingly harder for laypersons to determine the veracity of online health information. This is because of the explosion of content in health social media, allowing anyone with an Internet connection to create and propagate health-related content. This includes both innocuous and...
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Fall 2019
We present two provably optimal differentially private algorithms for the stochastic multi-arm bandit problem, as opposed to the private analogue of the UCB-algorithm (Mishra and Thakurta 2015; Tossou and Dimitrakakis 2016) which doesn’t meet the recently discovered lower-bound of Ω( K log(T) /...