Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Keeping AI Legal
AI programs make numerous decisions on their own, lack transparency, and may change frequently. Hence, the article shows, unassisted human agents — such as auditors, accountants, inspectors, and…
Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach
Many real world applications in medicine, biology, communication networks, web mining, and economics, among others, involve modeling and learning structured stochastic processes that evolve over…
Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
What capabilities are required for an AI system to pass standard 4th Grade Science Tests? Previous work has examined the use of Markov Logic Networks (MLNs) to represent the requisite background…
Selecting Near-Optimal Learners via Incremental Data Allocation
We study a novel machine learning (ML) problem setting of sequentially allocating small subsets of training data amongst a large set of classifiers. The goal is to select a classifier that will give…
Closing the Gap Between Short and Long XORs for Model Counting
Many recent algorithms for approximate model counting are based on a reduction to combinatorial searches over random subsets of the space defined by parity or XOR constraints. Long parity…
Exact Sampling with Integer Linear Programs and Random Perturbations
We consider the problem of sampling from a discrete probability distribution specified by a graphical model. Exact samples can, in principle, be obtained by computing the mode of the original model…
Hierarchical Semi-supervised Classification with Incomplete Class Hierarchies
In an entity classification task, topic or concept hierarchies are often incomplete. Previous work by Dalvi et al. has shown that in non-hierarchical semi-supervised classification tasks, the…
Segment-Phrase Table for Semantic Segmentation, Visual Entailment and Paraphrasing
We introduce Segment-Phrase Table (SPT), a large collection of bijective associations between textual phrases and their corresponding segmentations. Leveraging recent progress in object recognition…
Solving Geometry Problems: Combining Text and Diagram Interpretation
This paper introduces GeoS, the first automated system to solve unaltered SAT geometry questions by combining text understanding and diagram interpretation. We model the problem of understanding…
Generating Notifications for Missing Actions: Don’t forget to turn the lights off!
We all have experienced forgetting habitual actions among our daily activities. For example, we probably have forgotten to turn the lights off before leaving a room or turn the stove off after…