Ashish Tiwari

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Microsoft ∙ Stony Brook University

Information-theoretic User Interaction: Significant Inputs for Program Synthesis

Programming-by-example technologies are being deployed in industrial pro...
06/22/2020 ∙ by Ashish Tiwari, et al. ∙ 0 ∙ share

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Learning Distributed Controllers for V-Formation

We show how a high-performing, fully distributed and symmetric neural V-...
06/01/2020 ∙ by Shouvik Roy, et al. ∙ 0 ∙ share

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Data Invariants: On Trust in Data-Driven Systems

The reliability and proper function of data-driven applications hinge on...
03/03/2020 ∙ by Anna Fariha, et al. ∙ 0 ∙ share

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V-Formation via Model Predictive Control

We present recent results that demonstrate the power of viewing the prob...
02/20/2020 ∙ by Radu Grosu, et al. ∙ 0 ∙ share

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Quantitative Programming by Examples

Programming-by-Example (PBE) systems synthesize an intended program in s...
09/12/2019 ∙ by Sumit Gulwani, et al. ∙ 0 ∙ share

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Neural Flocking: MPC-based Supervised Learning of Flocking Controllers

We show how a distributed flocking controller can be synthesized using d...
08/26/2019 ∙ by Shouvik Roy, et al. ∙ 0 ∙ share

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SOTER: Programming Safe Robotics System using Runtime Assurance

Autonomous robots increasingly depend on third-party off-the-shelf compo...
08/23/2018 ∙ by Ankush Desai, et al. ∙ 0 ∙ share

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Adaptive Neighborhood Resizing for Stochastic Reachability in Multi-Agent Systems

We present DAMPC, a distributed, adaptive-horizon and adaptive-neighborh...
05/21/2018 ∙ by Anna Lukina, et al. ∙ 0 ∙ share

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Declarative vs Rule-based Control for Flocking Dynamics

The popularity of rule-based flocking models, such as Reynolds' classic ...
10/27/2017 ∙ by Usama Mehmood, et al. ∙ 0 ∙ share

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Specification Inference from Demonstrations

Learning from expert demonstrations has received a lot of attention in a...
10/11/2017 ∙ by Marcell Vazquez-Chanlatte, et al. ∙ 0 ∙ share

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Output Range Analysis for Deep Neural Networks

Deep neural networks (NN) are extensively used for machine learning task...
09/26/2017 ∙ by Souradeep Dutta, et al. ∙ 0 ∙ share

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ARES: Adaptive Receding-Horizon Synthesis of Optimal Plans

We introduce ARES, an efficient approximation algorithm for generating o...
12/21/2016 ∙ by Anna Lukina, et al. ∙ 0 ∙ share

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Ashish Tiwari

Featured Co-authors

Sanjit A. Seshia

Radu Grosu

Ezio Bartocci

Scott A. Smolka

Scott D. Stoller

Shromona Ghosh

Susmit Jha

Alexandra Meliou

Shan Lin

Sumit Gulwani

Nicola Paoletti

Information-theoretic User Interaction: Significant Inputs for Program Synthesis

Learning Distributed Controllers for V-Formation

Data Invariants: On Trust in Data-Driven Systems

V-Formation via Model Predictive Control

Quantitative Programming by Examples

Neural Flocking: MPC-based Supervised Learning of Flocking Controllers

SOTER: Programming Safe Robotics System using Runtime Assurance

Adaptive Neighborhood Resizing for Stochastic Reachability in Multi-Agent Systems

Declarative vs Rule-based Control for Flocking Dynamics

Specification Inference from Demonstrations

Output Range Analysis for Deep Neural Networks

ARES: Adaptive Receding-Horizon Synthesis of Optimal Plans