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2020 – today
- 2024
- [j14]Alvaro Velasquez, Ismail Alkhouri, Andre Beckus, Ashutosh Trivedi, George K. Atia:
Controller synthesis for linear temporal logic and steady-state specifications. Auton. Agents Multi Agent Syst. 38(1): 17 (2024) - [j13]Alvaro Velasquez, Piotr Wojciechowski, K. Subramani
, Matthew D. Williamson:
Arc-dependent networks: theoretical insights and a computational study. Ann. Oper. Res. 338(2): 1101-1126 (2024) - [j12]Piotr Wojciechowski, K. Subramani
Priority-based bin packing with subset constraints. Discret. Appl. Math. 342: 64-75 (2024) - [j11]Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou:
Robust Average-Reward Reinforcement Learning. J. Artif. Intell. Res. 80: 719-803 (2024) - [j10]K. Subramani, Piotr Wojciechowski, Alvaro Velasquez:
Farkas Bounds on Horn Constraint Systems. Theory Comput. Syst. 68(2): 227-249 (2024) - [j9]Kamal Acharya
Neurosymbolic Reinforcement Learning and Planning: A Survey. IEEE Trans. Artif. Intell. 5(5): 1939-1953 (2024) - [j8]Ismail R. Alkhouri
Exploring the Predictive Capabilities of AlphaFold Using Adversarial Protein Sequences. IEEE Trans. Artif. Intell. 5(7): 3384-3392 (2024) - [j7]Justus Renkhoff
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence. IEEE Trans. Artif. Intell. 5(8): 3765-3779 (2024) - [c69]Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Alvaro Velasquez:
Assume-Guarantee Reinforcement Learning. AAAI 2024: 21223-21231 - [c68]Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, Jivko Sinapov:
LgTS: Dynamic Task Sampling using LLM-generated Sub-Goals for Reinforcement Learning Agents. AAMAS 2024: 1736-1744 - [c67]Calvin Nau
An Exploration of Optimizing Kidney Exchanges with Graph Machine Learning. CogSIMA 2024: 114-119 - [c66]Sumit Kumar Jha
On the Design of Novel Attention Mechanism for Enhanced Efficiency of Transformers. DAC 2024: 315:1-315:6 - [c65]Abhinav Rajvanshi, Karan Sikka, Xiao Lin, Bhoram Lee, Han-Pang Chiu, Alvaro Velasquez:
SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments. ICAPS 2024: 464-474 - [c64]Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov:
Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. ICAPS 2024: 532-540 - [c63]Sangram Kishor Jena, K. Subramani, Alvaro Velasquez:
A Differential Approach for Several NP-hard Optimization Problems. ISAIM 2024: 68-80 - [c62]Susmit Jha, Sumit Kumar Jha, Alvaro Velasquez:
Neuro-symbolic Generative AI Assistant for System Design. MEMOCODE 2024: 75-76 - [i45]Justus Renkhoff, Ke Feng, Marc Meier-Doernberg, Alvaro Velasquez, Houbing Herbert Song:
A Survey on Verification and Validation, Testing and Evaluations of Neurosymbolic Artificial Intelligence. CoRR abs/2401.03188 (2024) - [i44]Yash Shukla, Tanushree Burman, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov:
Logical Specifications-guided Dynamic Task Sampling for Reinforcement Learning Agents. CoRR abs/2402.03678 (2024) - [i43]Prathyush Poduval, Zhuowen Zou, Alvaro Velasquez, Mohsen Imani:
Hyperdimensional Quantum Factorization. CoRR abs/2406.11889 (2024) - [i42]Noah Topper, Alvaro Velasquez, George K. Atia:
Bayesian Inverse Reinforcement Learning for Non-Markovian Rewards. CoRR abs/2406.13991 (2024) - [i41]Ismail Alkhouri, Cedric Le Denmat, Yingjie Li, Cunxi Yu, Jia Liu, Rongrong Wang, Alvaro Velasquez:
Dataless Quadratic Neural Networks for the Maximum Independent Set Problem. CoRR abs/2406.19532 (2024) - [i40]Walt Woods, Alexander Grushin, Simon Khan, Alvaro Velasquez:
Combining AI Control Systems and Human Decision Support via Robustness and Criticality. CoRR abs/2407.03210 (2024) - [i39]Kamal Acharya, Alvaro Velasquez, Yongxin Liu, Dahai Liu, Liang Sun, Houbing Song:
Improving Air Mobility for Pre-Disaster Planning with Neural Network Accelerated Genetic Algorithm. CoRR abs/2408.00790 (2024) - [i38]Lekai Chen, Ashutosh Trivedi, Alvaro Velasquez:
LLMs as Probabilistic Minimally Adequate Teachers for DFA Learning. CoRR abs/2408.02999 (2024) - [i37]Kamal Acharya, Alvaro Velasquez, Houbing Herbert Song:
A Survey on Symbolic Knowledge Distillation of Large Language Models. CoRR abs/2408.10210 (2024) - [i36]Joshua Pickard, Marc Andrew Choi, Natalie Oliven, Cooper Stansbury, Jillian Cwycyshyn, Nicholas Galioto, Alex A. Gorodetsky, Alvaro Velasquez, Indika Rajapakse:
Bioinformatics Retrieval Augmentation Data (BRAD) Digital Assistant. CoRR abs/2409.02864 (2024) - [i35]Hairi, Minghong Fang, Zifan Zhang, Alvaro Velasquez, Jia Liu:
On the Hardness of Decentralized Multi-Agent Policy Evaluation under Byzantine Attacks. CoRR abs/2409.12882 (2024) - [i34]Alexander Grushin, Walt Woods, Alvaro Velasquez, Simon Khan:
Criticality and Safety Margins for Reinforcement Learning. CoRR abs/2409.18289 (2024) - 2023
- [j6]Piotr Wojciechowski
Reachability in choice networks. Discret. Optim. 48(Part 1): 100761 (2023) - [j5]Alvaro Velasquez, K. Subramani
Reachability problems in interval-constrained and cardinality-constrained graphs. Discret. Math. Algorithms Appl. 15(4): 2250110:1-2250110:26 (2023) - [j4]Alvaro Velasquez, Ismail Alkhouri, K. Subramani
Optimal Deterministic Controller Synthesis from Steady-State Distributions. J. Autom. Reason. 67(1): 7 (2023) - [c61]Yue Wang
Robust Average-Reward Markov Decision Processes. AAAI 2023: 15215-15223 - [c60]Yash Shukla, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov:
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents. ICAPS 2023: 605-613 - [c59]Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu:
Resilient Distributed Optimization*. ACC 2023: 1307-1312 - [c58]Mohammad Afzal, Sankalp Gambhir, Ashutosh Gupta, S. Krishna, Ashutosh Trivedi, Alvaro Velasquez:
LTL-Based Non-Markovian Inverse Reinforcement Learning. AAMAS 2023: 2857-2859 - [c57]Jingxuan Zhu, Alvaro Velasquez, Ji Liu:
A Resilient Distributed Algorithm for Solving Linear Equations. CDC 2023: 381-386 - [c56]Sangram Kishor Jena, K. Subramani, Alvaro Velasquez:
Differentiable Discrete Optimization Using Dataless Neural Networks. COCOA (2) 2023: 3-15 - [c55]Stanley Bak
The Octatope Abstract Domain for Verification of Neural Networks. FM 2023: 454-472 - [c54]Wenkai Tan, Justus Renkhoff
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks. FUZZ 2023: 1-8 - [c53]Susmit Jha, Sumit Kumar Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Sandeep Neema
Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting. ICAA 2023: 149-152 - [c52]Lijing Zhu, Qizhen Lan, Alvaro Velasquez, Houbing Song, Acharya Kamal
SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection. ICDM (Workshops) 2023: 1186-1193 - [c51]Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou:
Model-Free Robust Average-Reward Reinforcement Learning. ICML 2023: 36431-36469 - [c50]Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia:
A Non-Targeted Attack Approach for the Coarse Misclassification Problem. IJCNN 2023: 1-7 - [c49]Sumit Kumar Jha, Susmit Jha, Rickard Ewetz, Alvaro Velasquez:
Neural SDEs for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. MILCOM 2023: 655-660 - [c48]Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema:
Counterexample Guided Inductive Synthesis Using Large Language Models and Satisfiability Solving. MILCOM 2023: 944-949 - [d1]Milad Kazemi Mehrabadi
Artifact for "Assume-Guarantee Reinforcement Learning". Zenodo, 2023 - [i33]Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou:
Robust Average-Reward Markov Decision Processes. CoRR abs/2301.00858 (2023) - [i32]Ismail Alkhouri, Sumit Kumar Jha, Andre Beckus, George K. Atia, Alvaro Velasquez, Rickard Ewetz, Arvind Ramanathan, Susmit Jha:
On the Robustness of AlphaFold: A COVID-19 Case Study. CoRR abs/2301.04093 (2023) - [i31]Lijing Zhu, Qizhen Lan, Alvaro Velasquez, Houbing Song, Acharya Kamal, Qing Tian, Shuteng Niu:
SKGHOI: Spatial-Semantic Knowledge Graph for Human-Object Interaction Detection. CoRR abs/2303.04253 (2023) - [i30]Justus Renkhoff, Wenkai Tan, Alvaro Velasquez, William Yichen Wang, Yongxin Liu, Jian Wang, Shuteng Niu, Lejla Begic Fazlic, Guido Dartmann, Houbing Song:
Exploring Adversarial Attacks on Neural Networks: An Explainable Approach. CoRR abs/2303.06032 (2023) - [i29]Wenkai Tan, Justus Renkhoff
NoiseCAM: Explainable AI for the Boundary Between Noise and Adversarial Attacks. CoRR abs/2303.06151 (2023) - [i28]Jingxuan Zhu, Alvaro Velasquez, Ji Liu:
A Resilient Distributed Algorithm for Solving Linear Equations. CoRR abs/2304.00373 (2023) - [i27]Yash Shukla, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, Jivko Sinapov:
Automaton-Guided Curriculum Generation for Reinforcement Learning Agents. CoRR abs/2304.05271 (2023) - [i26]Yue Wang, Alvaro Velasquez, George K. Atia, Ashley Prater-Bennette, Shaofeng Zou:
Model-Free Robust Average-Reward Reinforcement Learning. CoRR abs/2305.10504 (2023) - [i25]Alexander Grushin, Walt Woods, Alvaro Velasquez, Simon Khan:
Safety Margins for Reinforcement Learning. CoRR abs/2307.13642 (2023) - [i24]Kamal Acharya
Neurosymbolic Reinforcement Learning and Planning: A Survey. CoRR abs/2309.01038 (2023) - [i23]Abhinav Rajvanshi, Karan Sikka, Xiao Lin, Bhoram Lee, Han-Pang Chiu, Alvaro Velasquez:
SayNav: Grounding Large Language Models for Dynamic Planning to Navigation in New Environments. CoRR abs/2309.04077 (2023) - [i22]Sumit Kumar Jha, Susmit Jha, Rickard Ewetz, Alvaro Velasquez:
Neural Stochastic Differential Equations for Robust and Explainable Analysis of Electromagnetic Unintended Radiated Emissions. CoRR abs/2309.15386 (2023) - [i21]Sumit Kumar Jha, Susmit Jha, Patrick Lincoln, Nathaniel D. Bastian, Alvaro Velasquez, Rickard Ewetz, Sandeep Neema
Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving. CoRR abs/2309.16436 (2023) - [i20]Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu:
Byzantine-Resilient Decentralized Multi-Armed Bandits. CoRR abs/2310.07320 (2023) - [i19]Yash Shukla, Wenchang Gao, Vasanth Sarathy, Alvaro Velasquez, Robert Wright, Jivko Sinapov:
LgTS: Dynamic Task Sampling using LLM-generated sub-goals for Reinforcement Learning Agents. CoRR abs/2310.09454 (2023) - [i18]Suraj Singireddy, Andre Beckus, George K. Atia, Sumit Kumar Jha, Alvaro Velasquez:
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning. CoRR abs/2310.19137 (2023) - [i17]Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Alvaro Velasquez:
Assume-Guarantee Reinforcement Learning. CoRR abs/2312.09938 (2023) - 2022
- [j3]Ismail R. Alkhouri
A differentiable approach to the maximum independent set problem using dataless neural networks. Neural Networks 155: 168-176 (2022) - [j2]Alvaro Velasquez, K. Subramani
On the complexity of and solutions to the minimum stopping and trapping set problems. Theor. Comput. Sci. 915: 26-44 (2022) - [c47]Sumit Kumar Jha, Rickard Ewetz
Shaping Noise for Robust Attributions in Neural Stochastic Differential Equations. AAAI 2022: 9567-9574 - [c46]Ismail R. Alkhouri, Stanley Bak, Alvaro Velasquez, George K. Atia:
On the Coarse Robustness of Classifiers. IEEECONF 2022: 569-573 - [c45]Taylor Dohmen, Noah Topper, George K. Atia, Andre Beckus, Ashutosh Trivedi, Alvaro Velasquez:
Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning. ICAPS 2022: 574-582 - [c44]Noah Topper, George K. Atia, Ashutosh Trivedi, Alvaro Velasquez:
Active Grammatical Inference for Non-Markovian Planning. ICAPS 2022: 647-651 - [c43]Alvaro Velasquez, Brett Bissey, Lior Barak, Daniel Melcer, Andre Beckus, Ismail Alkhouri, George K. Atia:
Multi-Agent Tree Search with Dynamic Reward Shaping. ICAPS 2022: 652-661 - [c42]K. Subramani, Piotr Wojciechowski, Alvaro Velasquez:
New Results in Priority-Based Bin Packing. ALGOCLOUD 2022: 58-72 - [c41]Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu:
Resilient Constrained Consensus over Complete Graphs via Feasibility Redundancy. ACC 2022: 3418-3422 - [c40]Milad Kazemi, Mateo Perez, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Alvaro Velasquez:
Translating Omega-Regular Specifications to Average Objectives for Model-Free Reinforcement Learning. AAMAS 2022: 732-741 - [c39]Alvaro Velasquez, Ismail Alkhouri, Andre Beckus, Ashutosh Trivedi, George K. Atia:
Controller Synthesis for Omega-Regular and Steady-State Specifications. AAMAS 2022: 1310-1318 - [c38]Piotr Wojciechowski, K. Subramani, Alvaro Velasquez, Matthew D. Williamson:
On the Approximability of Path and Cycle Problems in Arc-Dependent Networks. CALDAM 2022: 292-304 - [c37]Piotr Wojciechowski, K. Subramani, Alvaro Velasquez:
Analyzing the Reachability Problem in Choice Networks. CPAIOR 2022: 408-423 - [c36]Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia:
Synthesis of Adversarial Samples in Two-Stage Classifiers. ICASSP 2022: 4248-4252 - [c35]Sumit Kumar Jha, Alvaro Velasquez, Rickard Ewetz
ExplainIt!: A Tool for Computing Robust Attributions of DNNs. IJCAI 2022: 5916-5919 - [c34]Justus Renkhoff
Exploring Adversarial Attacks on Neural Networks: An Explainable Approach. IPCCC 2022: 41-42 - [c33]Zenan Sun, Jingyi Su, Donghyun Jeon, Alvaro Velasquez, Houbing Song
Reinforced Contrastive Graph Neural Networks (RCGNN) for Anomaly Detection. IPCCC 2022: 65-72 - [c32]Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez:
A Differentiable Approach to the Maximum Independent Set Problem Using Graph-Based Neural Network Structures. MLSP 2022: 1-6 - [c31]Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia:
BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples. MLSP 2022: 1-6 - [c30]Alvaro Velasquez, Ismail R. Alkhouri, Brett Bissey, Lior Barak, George K. Atia:
The Minimum Value State Problem in Actor-Critic Networks. MLSP 2022: 1-7 - [c29]Yudan Wang, Yue Wang, Yi Zhou, Alvaro Velasquez, Shaofeng Zou:
Data-Driven Robust Multi-Agent Reinforcement Learning. MLSP 2022: 1-6 - [i16]Ismail R. Alkhouri, George K. Atia, Alvaro Velasquez:
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks. CoRR abs/2203.08209 (2022) - [i15]Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu:
Resilient Constrained Consensus over Complete Graphs via Feasibility Redundancy. CoRR abs/2203.14123 (2022) - [i14]Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu:
Resilient Distributed Optimization. CoRR abs/2209.13095 (2022) - 2021
- [j1]George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez:
Steady-State Planning in Expected Reward Multichain MDPs. J. Artif. Intell. Res. 72: 1029-1082 (2021) - [c28]Alvaro Velasquez, Brett Bissey, Lior Barak, Andre Beckus, Ismail Alkhouri, Daniel Melcer, George K. Atia:
Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search. AAAI 2021: 12015-12023 - [c27]Piotr Wojciechowski, K. Subramani, Alvaro Velasquez, Bugra Çaskurlu:
Algorithmic Analysis of Priority-Based Bin Packing. CALDAM 2021: 359-372 - [c26]Jing Wang, Elias Wilson, Alvaro Velasquez:
Consensus-Based Value Iteration for Multiagent Cooperative Control. CDC 2021: 6659-6664 - [c25]K. Subramani, Piotr Wojciechowski, Alvaro Velasquez:
On the Copy Complexity of Width 3 Horn Constraint Systems. FroCoS 2021: 63-78 - [c24]Sumit Kumar Jha, Rickard Ewetz
On Smoother Attributions using Neural Stochastic Differential Equations. IJCAI 2021: 522-528 - [c23]Alvaro Velasquez, Sumit Kumar Jha
Automated Synthesis of Quantum Circuits Using Symbolic Abstractions and Decision Procedures. ISCAS 2021: 1-5 - [c22]Ismail R. Alkhouri, Alvaro Velasquez, George K. Atia:
Adversarial Perturbation Attacks on Nested Dichotomies Classification Systems. MLSP 2021: 1-6 - [i13]Alvaro Velasquez, Ashutosh Trivedi, Ismail Alkhouri, Andre Beckus, George K. Atia:
Controller Synthesis for Omega-Regular and Steady-State Specifications. CoRR abs/2106.02951 (2021) - [i12]Alvaro Velasquez, Andre Beckus, Taylor Dohmen, Ashutosh Trivedi, Noah Topper, George K. Atia:
Learning Probabilistic Reward Machines from Non-Markovian Stochastic Reward Processes. CoRR abs/2107.04633 (2021) - [i11]Ismail Alkhouri, Alvaro Velasquez, George K. Atia:
BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples. CoRR abs/2108.02756 (2021) - [i10]Edward Verenich, Tobias Martin, Alvaro Velasquez, Nazar Khan, Faraz Hussain:
Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks. CoRR abs/2109.00573 (2021) - [i9]Sumit Kumar Jha, Arvind Ramanathan, Rickard Ewetz, Alvaro Velasquez, Susmit Jha:
Protein Folding Neural Networks Are Not Robust. CoRR abs/2109.04460 (2021) - 2020
- [c21]Alvaro Velasquez, Daniel Melcer:
Verification-Guided Tree Search. AAMAS 2020: 2026-2028 - [c20]Edward Verenich
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia. ICMLA 2020: 1402-1409 - [c19]George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez:
Steady-State Policy Synthesis in Multichain Markov Decision Processes. IJCAI 2020: 4069-4075 - [c18]Christopher H. Bennett, T. Patrick Xiao, Can Cui, Naimul Hassan, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Alvaro Velasquez, Joseph S. Friedman, Matthew J. Marinella:
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning. ISCAS 2020: 1-5 - [c17]Edward Verenich
FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints. OpML 2020 - [i8]Edward Verenich, Alvaro Velasquez, M. G. Sarwar Murshed, Faraz Hussain:
FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints. CoRR abs/2003.01538 (2020) - [i7]Christopher H. Bennett, T. Patrick Xiao, Can Cui, Naimul Hassan, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Alvaro Velasquez, Joseph S. Friedman, Matthew J. Marinella:
Plasticity-Enhanced Domain-Wall MTJ Neural Networks for Energy-Efficient Online Learning. CoRR abs/2003.02357 (2020) - [i6]Edward Verenich, Alvaro Velasquez, M. G. Sarwar Murshed, Faraz Hussain:
The Utility of Feature Reuse: Transfer Learning in Data-Starved Regimes. CoRR abs/2003.04117 (2020) - [i5]Alvaro Velasquez, Christopher H. Bennett, Naimul Hassan, Wesley H. Brigner, Otitoaleke G. Akinola, Jean Anne C. Incorvia, Matthew J. Marinella, Joseph S. Friedman:
Unsupervised Competitive Hardware Learning Rule for Spintronic Clustering Architecture. CoRR abs/2003.11120 (2020) - [i4]Edward Verenich, Alvaro Velasquez, Nazar Khan, Faraz Hussain:
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia. CoRR abs/2008.02866 (2020) - [i3]Sumit Kumar Jha, Susmit Jha, Rickard Ewetz, Sunny Raj, Alvaro Velasquez, Laura L. Pullum, Ananthram Swami:
An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks. CoRR abs/2009.08097 (2020) - [i2]Wesley H. Brigner, Naimul Hassan, Xuan Hu, Christopher H. Bennett, Felipe García-Sánchez, Can Cui, Alvaro Velasquez, Matthew J. Marinella, Jean Anne C. Incorvia, Joseph S. Friedman:
Domain Wall Leaky Integrate-and-Fire Neurons with Shape-Based Configurable Activation Functions. CoRR abs/2011.06075 (2020) - [i1]George K. Atia, Andre Beckus, Ismail Alkhouri, Alvaro Velasquez:
Verifiable Planning in Expected Reward Multichain MDPs. CoRR abs/2012.02178 (2020)
2010 – 2019
- 2019
- [c16]Mesut Ozdag, Sunny Raj, Steven Lawrence Fernandes, Alvaro Velasquez, Laura Pullum, Sumit Kumar Jha:
On the Susceptibility of Deep Neural Networks to Natural Perturbations. AISafety@IJCAI 2019 - [c15]Alvaro Velasquez:
Steady-State Policy Synthesis for Verifiable Control. IJCAI 2019: 5653-5661 - [c14]Alvaro Velasquez, Benjamin Shaia:
Spatially Efficient In-Memory Addition Through Destructive and Non-Destructive Operations. ISCAS 2019: 1-5 - 2018
- [c13]K. Subramani, Bugra Çaskurlu, Alvaro Velasquez:
Minimization of Testing Costs in Capacity-Constrained Database Migration. ALGOCLOUD 2018: 1-12 - [c12]Alvaro Velasquez, Sumit Kumar Jha
In-memory computing using paths-based logic and heterogeneous components. DATE 2018: 1512-1515 - [c11]Alvaro Velasquez, Sumit Kumar Jha
3D Crosspoint Memory as a Parallel Architecture for Computing Network Reachability. ICCD 2018: 171-178 - [c10]Alvaro Velasquez, K. Subramani, Steven L. Drager:
Finding Minimum Stopping and Trapping Sets: An Integer Linear Programming Approach. ISCO 2018: 402-415 - [c9]Alvaro Velasquez, Sumit Kumar Jha
Brief Announcement: Parallel Transitive Closure Within 3D Crosspoint Memory. SPAA 2018: 95-98 - 2017
- [c8]Alvaro Velasquez, Sumit Kumar Jha
Computation of Boolean matrix chain products in 3D ReRAM. ISCAS 2017: 1-4 - 2016
- [c7]Zahiruddin Alamgir
Flow-based computing on nanoscale crossbars: Design and implementation of full adders. ISCAS 2016: 1870-1873 - [c6]Alvaro Velasquez, Sumit Kumar Jha
Parallel boolean matrix multiplication in linear time using rectifying memristors. ISCAS 2016: 1874-1877 - [c5]Alvaro Velasquez, Piotr Wojciechowski
The cardinality-constrained paths problem: Multicast data routing in heterogeneous communication networks. NCA 2016: 126-130 - 2015
- [c4]Alvaro Velasquez, Sumit Kumar Jha
Fault-tolerant in-memory crossbar computing using quantified constraint solving. ICCD 2015: 101-108 - [c3]Alvaro Velasquez, Sumit Kumar Jha
Automated synthesis of crossbars for nanoscale computing using formal methods. NANOARCH 2015: 130-136 - 2014
- [c2]Faraz Hussain, Alvaro Velasquez, Emily Sassano, Sumit Kumar Jha
Putting humpty-dumpty together: Mining causal mechanistic biochemical models from big data. ICCABS 2014: 1-6 - [c1]Alvaro Velasquez, Sumit Kumar Jha
Parallel computing using memristive crossbar networks: Nullifying the processor-memory bottleneck. IDT 2014: 147-152
Coauthor Index
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last updated on 2024-12-08 02:27 CET by the dblp team
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