Nicholas Ruozzi

According to our database, Nicholas Ruozzi authored at least 48 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation.

Yangxiao Lu, Jishnu Jaykumar P, Yunhui Guo, Nicholas Ruozzi, Yu Xiang

CoRR, 2024

Predictive Task Guidance with Artificial Intelligence in Augmented Reality.

Benjamin Rheault, Shivvrat Arya, Akshay Vyas, Jikai Wang, Rohith Peddi, Brett Benda, Vibhav Gogate, Nicholas Ruozzi, Yu Xiang, Eric D. Ragan

Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, 2024

Mean Shift Mask Transformer for Unseen Object Instance Segmentation.

Yangxiao Lu, Yuqiao Chen, Nicholas Ruozzi, Yu Xiang

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models.

Chiradeep Roy, Mahsan Nourani, Shivvrat Arya, Mahesh Shanbhag, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate

ACM Trans. Interact. Intell. Syst., December, 2023

CaptainCook4D: A dataset for understanding errors in procedural activities.

Rohith Peddi, Shivvrat Arya, Bharath Challa, Likhitha Pallapothula, Akshay Vyas, Jikai Wang, Qifan Zhang, Vasundhara Komaragiri, Eric D. Ragan, Nicholas Ruozzi, Yu Xiang, Vibhav Gogate

CoRR, 2023

Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction.

Yangxiao Lu, Ninad A. Khargonkar, Zesheng Xu, Charles Averill, Kamalesh Palanisamy, Kaiyu Hang, Yunhui Guo, Nicholas Ruozzi, Yu Xiang

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Identifying Virtual Reality Users Across Domain-Specific Tasks: A Systematic Investigation of Tracked Features for Assembly.

Alec G. Moore, Tiffany D. Do, Nicholas Ruozzi, Ryan P. McMahan

Proceedings of the IEEE International Symposium on Mixed and Augmented Reality, 2023

A New Modeling Framework for Continuous, Sequential Domains.

Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Markov Random Fields, Homomorphism Counting, and Sidorenko's Conjecture.

Péter Csikvári, Nicholas Ruozzi, Shahab Shams

IEEE Trans. Inf. Theory, 2022

Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs.

Hao Xiong, Yangxiao Lu, Nicholas Ruozzi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Conditionally Tractable Density Estimation using Neural Networks.

Hailiang Dong, Chiradeep Roy, Tahrima Rahman, Vibhav Gogate, Nicholas Ruozzi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Relational Neural Markov Random Fields.

Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Exploration of Feature Representations for Predicting Learning and Retention Outcomes in a VR Training Scenario.

Alec G. Moore, Ryan P. McMahan, Nicholas Ruozzi

Big Data Cogn. Comput., 2021

Personal Identifiability of User Tracking Data During VR Training.

Alec G. Moore, Ryan P. McMahan, Hailiang Dong, Nicholas Ruozzi

Proceedings of the IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, 2021

Personal Identifiability and Obfuscation of User Tracking Data From VR Training Sessions.

Alec G. Moore, Ryan P. McMahan, Hailiang Dong, Nicholas Ruozzi

Proceedings of the IEEE International Symposium on Mixed and Augmented Reality, 2021

Dynamic Cutset Networks.

Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition.

Mahsan Nourani, Chiradeep Roy, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate

CoRR, 2020

Extracting Velocity-Based User-Tracking Features to Predict Learning Gains in a Virtual Reality Training Application.

Alec G. Moore, Ryan P. McMahan, Hailiang Dong, Nicholas Ruozzi

Proceedings of the 2020 IEEE International Symposium on Mixed and Augmented Reality, 2020

General Purpose MRF Learning with Neural Network Potentials.

Hao Xiong, Nicholas Ruozzi

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Lifted Hybrid Variational Inference.

Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Learning Correlated Latent Representations with Adaptive Priors.

Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara

CoRR, 2019

One-Shot Inference in Markov Random Fields.

Hao Xiong, Yuanzhen Guo, Yibo Yang, Nicholas Ruozzi

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Explainable Activity Recognition in Videos.

Chiradeep Roy, Mahesh Shanbhag, Mahsan Nourani, Tahrima Rahman, Samia Kabir, Vibhav Gogate, Nicholas Ruozzi, Eric D. Ragan

Proceedings of the Joint Proceedings of the ACM IUI 2019 Workshops co-located with the 24th ACM Conference on Intelligent User Interfaces (ACM IUI 2019), 2019

Counting Homomorphisms in Bipartite Graphs.

Shahab Shams, Nicholas Ruozzi, Péter Csikvári

Proceedings of the IEEE International Symposium on Information Theory, 2019

Lifted Message Passing for Hybrid Probabilistic Inference.

Yuqiao Chen, Nicholas Ruozzi, Sriraam Natarajan

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Correlated Variational Auto-Encoders.

Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi

Proceedings of the 36th International Conference on Machine Learning, 2019

Marginal Inference in Continuous Markov Random Fields Using Mixtures.

Yuanzhen Guo, Hao Xiong, Nicholas Ruozzi

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Scalable Neural Network Compression and Pruning Using Hard Clustering and L1 Regularization.

Yibo Yang, Nicholas Ruozzi, Vibhav Gogate

CoRR, 2018

Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks.

Li Chou, Pracheta Sahoo, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Sparse Approximate Conic Hulls.

Greg Van Buskirk, Benjamin Raichel, Nicholas Ruozzi

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Efficient Inference for Untied MLNs.

Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case.

Nicholas Ruozzi

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Bethe Learning of Graphical Models via MAP Decoding.

Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

On Parameter Tying by Quantization.

Li Chou, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Bethe Learning of Conditional Random Fields via MAP Decoding.

Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara

CoRR, 2015

P2V: Effective Website Fingerprinting Using Vector Space Representations.

Khaled Al-Naami, Gbadebo Ayoade, Asim Siddiqui, Nicholas Ruozzi, Latifur Khan, Bhavani Thuraisingham

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Exactness of Approximate MAP Inference in Continuous MRFs.

Nicholas Ruozzi

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Making Pairwise Binary Graphical Models Attractive.

Nicholas Ruozzi, Tony Jebara

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Message-Passing Algorithms: Reparameterizations and Splittings.

Nicholas Ruozzi, Sekhar Tatikonda

IEEE Trans. Inf. Theory, 2013

Message-passing algorithms for quadratic minimization.

Nicholas Ruozzi, Sekhar Tatikonda

J. Mach. Learn. Res., 2013

Beyond Log-Supermodularity: Lower Bounds and the Bethe Partition Function.

Nicholas Ruozzi

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012

The Bethe Partition Function of Log-supermodular Graphical Models.

Nicholas Ruozzi

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Convergent message-passing algorithms in the presence of erasures.

Nicholas Ruozzi

Proceedings of the 50th Annual Allerton Conference on Communication, 2012

2010

Convergent and Correct Message Passing Schemes for Optimization Problems over Graphical Models.

Nicholas Ruozzi, Sekhar Tatikonda

Proceedings of the UAI 2010, 2010

Unconstrained minimization of quadratic functions via min-sum.

Nicholas Ruozzi, Sekhar Tatikonda

Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010

2009

Applications of Metric Coinduction

Dexter Kozen, Nicholas Ruozzi

Log. Methods Comput. Sci., 2009

Graph covers and quadratic minimization.

Nicholas Ruozzi, Justin Thaler, Sekhar Tatikonda

Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008

s-t paths using the min-sum algorithm.

Nicholas Ruozzi, Sekhar Tatikonda

Proceedings of the 46th Annual Allerton Conference on Communication, 2008