Search Results for author:
Found 12 papers, 4 papers with code
Dynamics of unfolded protein aggregation
Unfolded protein aggregation in cellular system is a problem causing various types of diseases depending on which type unfolded proteins aggregate.
Large-scale randomized experiment reveals machine learning helps people learn and remember more effectively
Our randomized controlled trial also reveals that the learners whose study sessions are optimized using machine learning are $\sim$50% more likely to return to the app within 4-7 days.
Classification of Cuisines from Sequentially Structured Recipes
These cuisines are characterized in terms of their substructures such as ingredients, cooking processes and utensils.
Can A User Anticipate What Her Followers Want?
As a result, she may feel compelled to use the feedback she receives to (re-)estimate her followers' preferences and decides which stories to share next to receive more (positive) feedback.
Learning to Crawl
Web crawling is the problem of keeping a cache of webpages fresh, i. e., having the most recent copy available when a page is requested.
Stochastic Optimal Control of Epidemic Processes in Networks
We approach the development of models and control strategies of susceptible-infected-susceptible (SIS) epidemic processes from the perspective of marked temporal point processes and stochastic optimal control of stochastic differential equations (SDEs) with jumps.
Deep Reinforcement Learning of Marked Temporal Point Processes
In this paper, we address the above problem from the perspective of deep reinforcement learning of marked temporal point processes, where both the actions taken by an agent and the feedback it receives from the environment are asynchronous stochastic discrete events characterized using marked temporal point processes.
On the Complexity of Opinions and Online Discussions
Sports, and the Newsroom app suggest that unidimensional opinion models may often be unable to accurately represent online discussions, provide insights into human judgements and opinions, and show that our framework is able to circumvent language nuances such as sarcasm or humor by relying on human judgements instead of textual analysis.
Steering Social Activity: A Stochastic Optimal Control Point Of View
At a network level, they may increase activity by incentivizing a few influential users to take more actions, which in turn will trigger additional actions by other users.
Optimizing Human Learning
Can we find the optimal reviewing schedule to maximize the benefits of spaced repetition?
Uncovering the Dynamics of Crowdlearning and the Value of Knowledge
In this paper, we present a probabilistic modeling framework of crowdlearning, which uncovers the evolution of a user's expertise over time by leveraging other users' assessments of her contributions.
RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks
Users in social networks whose posts stay at the top of their followers'{} feeds the longest time are more likely to be noticed.
