Search Results for author: Utkarsh Upadhyay

Found 13 papers, 5 papers with code

Dynamics of unfolded protein aggregation

no code implementations7 Nov 2021 Utkarsh Upadhyay, Chandrima Barua, Shivani Devi, Jay Prakash Kumar, R. K. Brojen Singh

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

1 code implementation9 Oct 2020 Utkarsh Upadhyay, Graham Lancashire, Christoph Moser, Manuel Gomez-Rodriguez

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.

BIG-bench Machine Learning

Classification of Cuisines from Sequentially Structured Recipes

no code implementations26 Apr 2020 Tript Sharma, Utkarsh Upadhyay, Ganesh Bagler

These cuisines are characterized in terms of their substructures such as ingredients, cooking processes and utensils.

Classification General Classification

Can A User Anticipate What Her Followers Want?

no code implementations1 Sep 2019 Abir De, Adish Singla, Utkarsh Upadhyay, Manuel Gomez-Rodriguez

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.

Decision Making Two-sample testing

Learning to Crawl

no code implementations29 May 2019 Utkarsh Upadhyay, Robert Busa-Fekete, Wojciech Kotlowski, David Pal, Balazs Szorenyi

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.

Enhancing human learning via spaced repetition optimization

1 code implementation Proceedings of the National Academy of Sciences (PNAS) 2019 Behzad Tabibian, Utkarsh Upadhyay, Abir De, Ali Zarezade, Bernhard Schölkopf, Manuel Gomez-Rodriguez

Spaced repetition is a technique for efficient memorization which uses repeated review of content following a schedule determined by a spaced repetition algorithm to improve long-term retention.

Memorization Point Processes

Stochastic Optimal Control of Epidemic Processes in Networks

no code implementations30 Oct 2018 Lars Lorch, Abir De, Samir Bhatt, William Trouleau, Utkarsh Upadhyay, Manuel Gomez-Rodriguez

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.

Point Processes

Deep Reinforcement Learning of Marked Temporal Point Processes

1 code implementation NeurIPS 2018 Utkarsh Upadhyay, Abir De, Manuel Gomez-Rodriguez

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.

Marketing Point Processes +3

On the Complexity of Opinions and Online Discussions

1 code implementation19 Feb 2018 Utkarsh Upadhyay, Abir De, Aasish Pappu, Manuel Gomez-Rodriguez

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

no code implementations19 Feb 2018 Ali Zarezade, Abir De, Utkarsh Upadhyay, Hamid R. Rabiee, Manuel Gomez-Rodriguez

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.

Point Processes

Uncovering the Dynamics of Crowdlearning and the Value of Knowledge

no code implementations14 Dec 2016 Utkarsh Upadhyay, Isabel Valera, Manuel Gomez-Rodriguez

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

1 code implementation18 Oct 2016 Ali Zarezade, Utkarsh Upadhyay, Hamid Rabiee, Manuel Gomez Rodriguez

Users in social networks whose posts stay at the top of their followers'{} feeds the longest time are more likely to be noticed.

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