Nicholas Ruozzi

65 papers A* 15A 11B 2Misc 1Journal 23Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	A Novel Approach to Evaluating Evaluation Metrics for Multi-Output Structured Prediction. AAAI Akshay Vyas, Angelo Pimienta, Nicholas Ruozzi
2026	J	`jnl`	Learnability-Driven Submodular Optimization for Active Roadside 3D Detection. CoRR Ruiyu Mao, Baoming Zhang, Nicholas Ruozzi, Yunhui Guo
2025	A	`conf`	Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation. IROS Yangxiao Lu, Jishnu Jaykumar P, Yunhui Guo, Nicholas Ruozzi, Yu Xiang
2025	J	`jnl`	Multimodal Reference Visual Grounding. CoRR Yangxiao Lu, Ruosen Li, Liqiang Jing, Jikai Wang, Xinya Du, Yunhui Guo, Nicholas Ruozzi, Yu Xiang
2024	J	`jnl`	Adapting Pre-Trained Vision Models for Novel Instance Detection and Segmentation. CoRR Yangxiao Lu, Jishnu Jaykumar P, Yunhui Guo, Nicholas Ruozzi, Yu Xiang
2024	A*	`conf`	CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities. NeurIPS Rohith Peddi, Shivvrat Arya, Bharath Challa, Likhitha Pallapothula, Akshay Vyas, Bhavya Gouripeddi, Qifan Zhang, Jikai Wang, Vasundhara Komaragiri, Eric D. Ragan, Nicholas Ruozzi, Yu Xiang, Vibhav Gogate
2024	A	`conf`	Learning Distributionally Robust Tractable Probabilistic Models in Continuous Domains. UAI Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi
2024	A*	`conf`	Mean Shift Mask Transformer for Unseen Object Instance Segmentation. ICRA Yangxiao Lu, Yuqiao Chen, Nicholas Ruozzi, Yu Xiang
2024	—	`conf`	Predictive Task Guidance with Artificial Intelligence in Augmented Reality. VR Workshops Benjamin Rheault, Shivvrat Arya, Akshay Vyas, Jikai Wang, Rohith Peddi, Brett Benda, Vibhav Gogate, Nicholas Ruozzi, Yu Xiang, Eric D. Ragan
2023	A	`conf`	A New Modeling Framework for Continuous, Sequential Domains. AISTATS Hailiang Dong, James Amato, Vibhav Gogate, Nicholas Ruozzi
2023	J	`jnl`	CaptainCook4D: A dataset for understanding errors in procedural activities. CoRR 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
2023	J	`jnl`	Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models. ACM Trans. Interact. Intell. Syst. Chiradeep Roy, Mahsan Nourani, Shivvrat Arya, Mahesh Shanbhag, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate
2023	A*	`conf`	Identifying Virtual Reality Users Across Domain-Specific Tasks: A Systematic Investigation of Tracked Features for Assembly. ISMAR Alec G. Moore, Tiffany D. Do, Nicholas Ruozzi, Ryan P. McMahan
2023	—	`conf`	Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction. Robotics: Science and Systems Yangxiao Lu, Ninad A. Khargonkar, Zesheng Xu, Charles Averill, Kamalesh Palanisamy, Kaiyu Hang, Yunhui Guo, Nicholas Ruozzi, Yu Xiang
2023	J	`jnl`	Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction. CoRR Yangxiao Lu, Ninad Khargonkar, Zesheng Xu, Charles Averill, Kamalesh Palanisamy, Kaiyu Hang, Yunhui Guo, Nicholas Ruozzi, Yu Xiang
2022	A*	`conf`	Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs. NeurIPS Hao Xiong, Yangxiao Lu, Nicholas Ruozzi
2022	A	`conf`	Conditionally Tractable Density Estimation using Neural Networks. AISTATS Hailiang Dong, Chiradeep Roy, Tahrima Rahman, Vibhav Gogate, Nicholas Ruozzi
2022	J	`jnl`	Markov Random Fields, Homomorphism Counting, and Sidorenko's Conjecture. IEEE Trans. Inf. Theory Péter Csikvári, Nicholas Ruozzi, Shahab Shams
2022	J	`jnl`	Mean Shift Mask Transformer for Unseen Object Instance Segmentation. CoRR Yangxiao Lu, Yuqiao Chen, Nicholas Ruozzi, Yu Xiang
2022	A	`conf`	Relational Neural Markov Random Fields. AISTATS Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi
2021	A	`conf`	Dynamic Cutset Networks. AISTATS Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate
2021	J	`jnl`	Exploration of Feature Representations for Predicting Learning and Retention Outcomes in a VR Training Scenario. Big Data Cogn. Comput. Alec G. Moore, Ryan P. McMahan, Nicholas Ruozzi
2021	A*	`conf`	Personal Identifiability and Obfuscation of User Tracking Data From VR Training Sessions. ISMAR Alec G. Moore, Ryan P. McMahan, Hailiang Dong, Nicholas Ruozzi
2021	—	`conf`	Personal Identifiability of User Tracking Data During VR Training. VR Workshops Alec G. Moore, Ryan P. McMahan, Hailiang Dong, Nicholas Ruozzi
2021	J	`jnl`	Relational Neural Markov Random Fields. CoRR Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi
2020	J	`jnl`	Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition. CoRR Mahsan Nourani, Chiradeep Roy, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate
2020	A*	`conf`	Extracting Velocity-Based User-Tracking Features to Predict Learning Gains in a Virtual Reality Training Application. ISMAR Alec G. Moore, Ryan P. McMahan, Hailiang Dong, Nicholas Ruozzi
2020	A*	`conf`	General Purpose MRF Learning with Neural Network Potentials. IJCAI Hao Xiong, Nicholas Ruozzi
2020	A*	`conf`	Lifted Hybrid Variational Inference. IJCAI Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi
2020	J	`jnl`	Lifted Hybrid Variational Inference. CoRR Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi
2019	—	`conf`	Correlated Variational Auto-Encoders. DGS@ICLR Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	A*	`conf`	Correlated Variational Auto-Encoders. ICML Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	J	`jnl`	Correlated Variational Auto-Encoders. CoRR Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi
2019	B	`conf`	Counting Homomorphisms in Bipartite Graphs. ISIT Shahab Shams, Nicholas Ruozzi, Péter Csikvári
2019	—	`conf`	Explainable Activity Recognition in Videos. IUI Workshops Chiradeep Roy, Mahesh Shanbhag, Mahsan Nourani, Tahrima Rahman, Samia Kabir, Vibhav Gogate, Nicholas Ruozzi, Eric D. Ragan
2019	J	`jnl`	Learning Correlated Latent Representations with Adaptive Priors. CoRR Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara
2019	A*	`conf`	Lifted Message Passing for Hybrid Probabilistic Inference. IJCAI Yuqiao Chen, Nicholas Ruozzi, Sriraam Natarajan
2019	A*	`conf`	Marginal Inference in Continuous Markov Random Fields Using Mixtures. AAAI Yuanzhen Guo, Hao Xiong, Nicholas Ruozzi
2019	A	`conf`	One-Shot Inference in Markov Random Fields. UAI Hao Xiong, Yuanzhen Guo, Yibo Yang, Nicholas Ruozzi
2018	A*	`conf`	Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks. AAAI Li Chou, Pracheta Sahoo, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate
2018	J	`jnl`	Scalable Neural Network Compression and Pruning Using Hard Clustering and L1 Regularization. CoRR Yibo Yang, Nicholas Ruozzi, Vibhav Gogate
2017	A	`conf`	A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case. AISTATS Nicholas Ruozzi
2017	A*	`conf`	Efficient Inference for Untied MLNs. IJCAI Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate
2017	—	`conf`	Sparse Approximate Conic Hulls. NIPS Greg Van Buskirk, Benjamin Raichel, Nicholas Ruozzi
2016	A	`conf`	Bethe Learning of Graphical Models via MAP Decoding. AISTATS Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
2016	A*	`conf`	On Parameter Tying by Quantization. AAAI Li Chou, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate
2015	J	`jnl`	Bethe Learning of Conditional Random Fields via MAP Decoding. CoRR Kui Tang, Nicholas Ruozzi, David Belanger, Tony Jebara
2015	—	`conf`	Exactness of Approximate MAP Inference in Continuous MRFs. NIPS Nicholas Ruozzi
2015	—	`conf`	P2V: Effective Website Fingerprinting Using Vector Space Representations. SSCI Khaled Al-Naami, Gbadebo Ayoade, Asim Siddiqui, Nicholas Ruozzi, Latifur Khan, Bhavani Thuraisingham
2014	—	`conf`	Making Pairwise Binary Graphical Models Attractive. NIPS Nicholas Ruozzi, Tony Jebara
2013	A	`conf`	Beyond Log-Supermodularity: Lower Bounds and the Bethe Partition Function. UAI Nicholas Ruozzi
2013	J	`jnl`	Beyond Log-Supermodularity: Lower Bounds and the Bethe Partition Function. CoRR Nicholas Ruozzi
2013	J	`jnl`	Message-Passing Algorithms: Reparameterizations and Splittings. IEEE Trans. Inf. Theory Nicholas Ruozzi, Sekhar Tatikonda
2013	J	`jnl`	Message-passing algorithms for quadratic minimization. J. Mach. Learn. Res. Nicholas Ruozzi, Sekhar Tatikonda
2012	—	`conf`	Convergent message-passing algorithms in the presence of erasures. Allerton Conference Nicholas Ruozzi
2012	J	`jnl`	Message-Passing Algorithms for Quadratic Minimization CoRR Nicholas Ruozzi, Sekhar Tatikonda
2012	J	`jnl`	The Bethe Partition Function of Log-supermodular Graphical Models CoRR Nicholas Ruozzi
2012	—	`conf`	The Bethe Partition Function of Log-supermodular Graphical Models. NIPS Nicholas Ruozzi
2010	J	`jnl`	Convergent and Correct Message Passing Schemes for Optimization Problems over Graphical Models CoRR Nicholas Ruozzi, Sekhar Tatikonda
2010	A	`conf`	Convergent and Correct Message Passing Schemes for Optimization Problems over Graphical Models. UAI Nicholas Ruozzi, Sekhar Tatikonda
2010	Misc	`conf`	Unconstrained minimization of quadratic functions via min-sum. CISS Nicholas Ruozzi, Sekhar Tatikonda
2009	J	`jnl`	Applications of Metric Coinduction Log. Methods Comput. Sci. Dexter Kozen, Nicholas Ruozzi
2009	—	`conf`	Graph covers and quadratic minimization. Allerton Nicholas Ruozzi, Justin Thaler, Sekhar Tatikonda
2008	—	`conf`	s-t paths using the min-sum algorithm. Allerton Nicholas Ruozzi, Sekhar Tatikonda
2007	B	`conf`	Applications of Metric Coinduction. CALCO Dexter Kozen, Nicholas Ruozzi