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07/13/2023
Retrieving Continuous Time Event Sequences using Neural Temporal Point Processes with Learnable Hashing
Temporal sequences have become pervasive in various real-world applicati...
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10/20/2022
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection
Submodular functions and variants, through their ability to characterize...
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10/20/2022
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks
The graph retrieval problem is to search in a large corpus of graphs for...
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06/23/2022
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes
A large fraction of data generated via human activities such as online p...
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02/17/2022
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences
Recent developments in predictive modeling using marked temporal point p...
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11/30/2021
Global Convergence Using Policy Gradient Methods for Model-free Markovian Jump Linear Quadratic Control
Owing to the growth of interest in Reinforcement Learning in the last fe...
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08/23/2021
Integrating Transductive And Inductive Embeddings Improves Link Prediction Accuracy
In recent years, inductive graph embedding models, viz., graph neural ne...
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08/15/2021
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time
In several real world applications, machine learning models are deployed...
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07/06/2021
Counterfactual Explanations in Sequential Decision Making Under Uncertainty
Methods to find counterfactual explanations have predominantly focused o...
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06/30/2021
Group Testing under Superspreading Dynamics
Testing is recommended for all close contacts of confirmed COVID-19 pati...
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06/23/2021
Training Data Subset Selection for Regression with Controlled Generalization Error
Data subset selection from a large number of training instances has been...
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03/16/2021
Differentiable Learning Under Triage
Multiple lines of evidence suggest that predictive models may benefit fr...
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02/11/2021
Demarcating Endogenous and Exogenous Opinion Dynamics: An Experimental Design Approach
The networked opinion diffusion in online social networks (OSN) is often...
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01/08/2021
Long Horizon Forecasting With Temporal Point Processes
In recent years, marked temporal point processes (MTPPs) have emerged as...
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12/13/2020
Adversarial Permutation Guided Node Representations for Link Prediction
After observing a snapshot of a social network, a link prediction (LP) a...
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06/21/2020
Classification Under Human Assistance
Most supervised learning models are trained for full automation. However...
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02/11/2020
Learning to Switch Between Machines and Humans
Reinforcement learning algorithms have been mostly developed and evaluat...
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09/06/2019
Regression Under Human Assistance
Decisions are increasingly taken by both humans and machine learning mod...
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09/01/2019
Can A User Guess What Her Followers Want?
Whenever a social media user decides to share a story, she is typically ...
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05/13/2019
Consequential Ranking Algorithms and Long-term Welfare
Ranking models are typically designed to provide rankings that optimize ...
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10/30/2018
Stochastic Optimal Control of Epidemic Processes in Networks
We approach the development of models and control strategies of suscepti...
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05/23/2018
Deep Reinforcement Learning of Marked Temporal Point Processes
In a wide variety of applications, humans interact with a complex enviro...
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02/19/2018
On the Complexity of Opinions and Online Discussions
In an increasingly polarized world, demagogues who reduce complexity dow...
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02/19/2018
Steering Social Activity: A Stochastic Optimal Control Point Of View
User engagement in online social networking depends critically on the le...
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02/14/2018
Designing Random Graph Models Using Variational Autoencoders With Applications to Chemical Design
Deep generative models have been praised for their ability to learn smoo...
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12/05/2017
Optimizing Human Learning
Spaced repetition is a technique for efficient memorization which uses r...
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03/06/2017