Yuriy Nevmyvaka

66 papers A* 14A 8B 1Misc 1Journal 37Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	GeoNorm: Unify Pre-Norm and Post-Norm with Geodesic Optimization. CoRR Chuanyang Zheng, Jiankai Sun, Yihang Gao, Chi Wang, Yuehao Wang, Jing Xiong, Liliang Ren, Bo Peng, Qingmei Wang, Xiaoran Shang, Mac Schwager, Anderson Schneider, Yuriy Nevmyvaka, Xiaodong Liu
2026	J	`jnl`	Hiding in Plain Text: Detecting Concealed Jailbreaks via Activation Disentanglement. CoRR Amirhossein Farzam, Majid Behabahani, Mani Malek, Yuriy Nevmyvaka, Guillermo Sapiro
2025	J	`jnl`	AHA: Aligning Large Audio-Language Models for Reasoning Hallucinations via Counterfactual Hard Negatives. CoRR Yanxi Chen, Wenhui Zhu, Xiwen Chen, Zhipeng Wang, Xin Li, Peijie Qiu, Hao Wang, Xuanzhao Dong, Yujian Xiong, Anderson Schneider, Yuriy Nevmyvaka, Yalin Wang
2025	J	`jnl`	Breaking the n CoRR Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2025	A*	`conf`	Breaking the n1.5 Additive Error Barrier for Private and Efficient Graph Sparsification via Private Expander Decomposition. ICML Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2025	J	`jnl`	Chart-RVR: Reinforcement Learning with Verifiable Rewards for Explainable Chart Reasoning. CoRR Sanchit Sinha, Oana Frunza, Kashif Rasul, Yuriy Nevmyvaka, Aidong Zhang
2025	J	`jnl`	Improving Reasoning for Diffusion Language Models via Group Diffusion Policy Optimization. CoRR Kevin Rojas, Jiahe Lin, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Molei Tao, Wei Deng
2025	—	`conf`	Multi-modal Time Series Analysis: A Tutorial and Survey. KDD (2) Yushan Jiang, Kanghui Ning, Zijie Pan, Xuyang Shen, Jingchao Ni, Wenchao Yu, Anderson Schneider, Haifeng Chen, Yuriy Nevmyvaka, Dongjin Song
2025	J	`jnl`	Multi-modal Time Series Analysis: A Tutorial and Survey. CoRR Yushan Jiang, Kanghui Ning, Zijie Pan, Xuyang Shen, Jingchao Ni, Wenchao Yu, Anderson Schneider, Haifeng Chen, Yuriy Nevmyvaka, Dongjin Song
2025	A*	`conf`	Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting. ICML Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann
2025	J	`jnl`	Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting. CoRR Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann
2025	J	`jnl`	Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting. CoRR Roland Riachi, Kashif Rasul, Arjun Ashok, Prateek Humane, Alexis Roger, Andrew Robert Williams, Yuriy Nevmyvaka, Irina Rish
2025	J	`jnl`	Reinforcing Multi-Turn Reasoning in LLM Agents via Turn-Level Credit Assignment. CoRR Siliang Zeng, Quan Wei, William Brown, Oana Frunza, Yuriy Nevmyvaka, Mingyi Hong
2025	J	`jnl`	Reweighting Improves Conditional Risk Bounds. CoRR Yikai Zhang, Jiahe Lin, Fengpei Li, Songzhu Zheng, Anant Raj, Anderson Schneider, Yuriy Nevmyvaka
2025	J	`jnl`	Reweighting Improves Conditional Risk Bounds. Trans. Mach. Learn. Res. Yikai Zhang, Jiahe Lin, Fengpei Li, Songzhu Zheng, Anant Raj, Anderson Schneider, Yuriy Nevmyvaka
2025	—	`conf`	Scaling Laws and Efficient Inference for Ternary Language Models. ACL (1) Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish
2025	J	`jnl`	Small Vocabularies, Big Gains: Pretraining and Tokenization in Time Series Models. CoRR Alexis Roger, Gwen Legate, Kashif Rasul, Yuriy Nevmyvaka, Irina Rish
2025	J	`jnl`	Spectra 1.1: Scaling Laws and Efficient Inference for Ternary Language Models. CoRR Tejas Vaidhya, Ayush Kaushal, Vineet Jain, Francis Couture Harpin, Prashant Shishodia, Majid Behbahani, Yuriy Nevmyvaka, Irina Rish
2025	J	`jnl`	Speculative Sampling for Parametric Temporal Point Processes. CoRR Marin Bilos, Anderson Schneider, Yuriy Nevmyvaka
2025	J	`jnl`	TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster. CoRR Kanghui Ning, Zijie Pan, Yu Liu, Yushan Jiang, James Y. Zhang, Kashif Rasul, Anderson Schneider, Lintao Ma, Yuriy Nevmyvaka, Dongjin Song
2025	J	`jnl`	Technical Report: Full-Stack Fine-Tuning for the Q Programming Language. CoRR Brendan R. Hogan, Will Brown, Adel Boyarsky, Anderson Schneider, Yuriy Nevmyvaka
2025	—	`conf`	The 11th Mining and Learning from Time Series (MILETS): From Classical Methods to LLMs. KDD (2) Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Yuxuan Liang, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka
2025	—	`conf`	Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision. ICDM (Workshops) Kanghui Ning, Zijie Pan, Yushan Jiang, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
2025	J	`jnl`	Towards Interpretable and Trustworthy Time Series Reasoning: A BlueSky Vision. CoRR Kanghui Ning, Zijie Pan, Yushan Jiang, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
2025	J	`jnl`	Understanding the Mixture-of-Experts with Nadaraya-Watson Kernel. CoRR Chuanyang Zheng, Jiankai Sun, Yihang Gao, Enze Xie, Yuehao Wang, Peihao Wang, Ting Xu, Matthew Chang, Liliang Ren, Jingyao Li, Jing Xiong, Kashif Rasul, Mac Schwager, Anderson Schneider, Zhangyang Wang, Yuriy Nevmyvaka
2025	A	`conf`	Variational Schrödinger Momentum Diffusion. AISTATS Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng
2025	J	`jnl`	Variational Schrödinger Momentum Diffusion. CoRR Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng
2024	J	`jnl`	Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. CoRR Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul, Yuriy Nevmyvaka, Sneihil Gopal, Amit Dhurandhar, Guillermo A. Cecchi, Irina Rish
2024	J	`jnl`	Differentially Private Gomory-Hu Trees. CoRR Anders Aamand, Justin Y. Chen, Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka, Sandeep Silwal, Yinzhan Xu
2024	A*	`conf`	Empowering Time Series Analysis with Large Language Models: A Survey. IJCAI Yushan Jiang, Zijie Pan, Xikun Zhang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
2024	J	`jnl`	Empowering Time Series Analysis with Large Language Models: A Survey. CoRR Yushan Jiang, Zijie Pan, Xikun Zhang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
2024	J	`jnl`	Graph Partitioning With Limited Moves. CoRR Majid Behbahani, Mina Dalirrooyfard, Elaheh Fata, Yuriy Nevmyvaka
2024	A	`conf`	Graph Partitioning with a Move Budget. AISTATS Mina Dalirrooyfard, Elaheh Fata, Majid Behbahani, Yuriy Nevmyvaka
2024	J	`jnl`	Learning to Abstain From Uninformative Data. Trans. Mach. Learn. Res. Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen
2024	J	`jnl`	Prediction-Enhanced Monte Carlo: A Machine Learning View on Control Variate. CoRR Fengpei Li, Haoxian Chen, Jiahe Lin, Arkin Gupta, Xiaowei Tan, Gang Xu, Yuriy Nevmyvaka, Agostino Capponi, Henry Lam
2024	J	`jnl`	S CoRR Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
2024	A*	`conf`	S2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting. ICML Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
2024	J	`jnl`	Structural Knowledge Informed Continual Multivariate Time Series Forecasting. CoRR Zijie Pan, Yushan Jiang, Dongjin Song, Sahil Garg, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka
2024	A*	`conf`	The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. KDD Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Stefan Zohren, Yuriy Nevmyvaka
2024	A*	`conf`	VQ-TR: Vector Quantized Attention for Time Series Forecasting. ICLR Kashif Rasul, Andrew Bennett, Pablo Vicente, Umang Gupta, Hena Ghonia, Anderson Schneider, Yuriy Nevmyvaka
2024	A*	`conf`	Variational Schrödinger Diffusion Models. ICML Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen
2024	J	`jnl`	Variational Schrödinger Diffusion Models. CoRR Wei Deng, Weijian Luo, Yixin Tan, Marin Bilos, Yu Chen, Yuriy Nevmyvaka, Ricky T. Q. Chen
2023	A	`conf`	Detection of Short-Term Temporal Dependencies in Hawkes Processes with Heterogeneous Background Dynamics. UAI Yu Chen, Fengpei Li, Anderson Schneider, Yuriy Nevmyvaka, Asohan Amarasingham, Henry Lam
2023	A	`conf`	In- or out-of-distribution detection via dual divergence estimation. UAI Sahil Garg, Sanghamitra Dutta, Mina Dalirrooyfard, Anderson Schneider, Yuriy Nevmyvaka
2023	A	`conf`	Information theoretic clustering via divergence maximization among clusters. UAI Sahil Garg, Mina Dalirrooyfard, Anderson Schneider, Yeshaya Adler, Yuriy Nevmyvaka, Yu Chen, Fengpei Li, Guillermo A. Cecchi
2023	J	`jnl`	Lag-Llama: Towards Foundation Models for Time Series Forecasting. CoRR Kashif Rasul, Arjun Ashok, Andrew Robert Williams, Arian Khorasani, George Adamopoulos, Rishika Bhagwatkar, Marin Bilos, Hena Ghonia, Nadhir Vincent Hassen, Anderson Schneider, Sahil Garg, Alexandre Drouin, Nicolas Chapados, Yuriy Nevmyvaka, Irina Rish
2023	J	`jnl`	Learning to Abstain From Uninformative Data. CoRR Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen
2023	A*	`conf`	Modeling Temporal Data as Continuous Functions with Stochastic Process Diffusion. ICML Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann
2023	J	`jnl`	Nearly Tight Bounds For Differentially Private Min s-t and Multiway Cut. CoRR Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka
2023	A*	`conf`	Nearly Tight Bounds For Differentially Private Multiway Cut. NeurIPS Mina Dalirrooyfard, Slobodan Mitrovic, Yuriy Nevmyvaka
2023	A*	`conf`	Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. ICML Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
2023	J	`jnl`	Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation. CoRR Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka
2023	A	`conf`	Risk Bounds on Aleatoric Uncertainty Recovery. AISTATS Yikai Zhang, Jiahe Lin, Fengpei Li, Yeshaya Adler, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka
2023	J	`jnl`	Short-term Temporal Dependency Detection under Heterogeneous Event Dynamic with Hawkes Processes. CoRR Yu Chen, Fengpei Li, Anderson Schneider, Yuriy Nevmyvaka, Asohan Amarasingham, Henry Lam
2023	A*	`conf`	The 9th SIGKDD International Workshop on Mining and Learning from Time Series. KDD Sanjay Purushotham, Dongjin Song, Qingsong Wen, Jun Huan, Cong Shen, Yuriy Nevmyvaka
2022	A*	`conf`	8th SIGKDD International Workshop on Mining and Learning from Time Series - Deep Forecasting: Models, Interpretability, and Applications. KDD Sanjay Purushotham, Jun Huan, Cong Shen, Dongjin Song, Yuyang Wang, Jan Gasthaus, Hilaf Hasson, Youngsuk Park, Sungyong Seo, Yuriy Nevmyvaka
2022	A	`conf`	Estimating transfer entropy under long ranged dependencies. UAI Sahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka
2022	J	`jnl`	Modeling Temporal Data as Continuous Functions with Process Diffusion. CoRR Marin Bilos, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, Stephan Günnemann
2021	—	`conf`	AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale. NeurIPS (Competition and Demos) Nicholas Roberts, Samuel Guo, Cong Xu, Ameet Talwalkar, David Lander, Lvfang Tao, Linhang Cai, Shuaicheng Niu, Jianyu Heng, Hongyang Qin, Minwen Deng, Johannes Hog, Alexander Pfefferle, Sushil Ammanaghatta Shivakumar, Arjun Krishnakumar, Yubo Wang, Rhea Sanjay Sukthanker, Frank Hutter, Euxhen Hasanaj, Tien-Dung Le, Mikhail Khodak, Yuriy Nevmyvaka, Kashif Rasul, Frederic Sala, Anderson Schneider, Junhong Shen, Evan Randall Sparks
2014	A*	`conf`	Pursuit-Evasion Without Regret, with an Application to Trading. ICML Lili Dworkin, Michael J. Kearns, Yuriy Nevmyvaka
2012	J	`jnl`	Censored Exploration and the Dark Pool Problem CoRR Kuzman Ganchev, Michael J. Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan
2010	J	`jnl`	Censored exploration and the dark pool problem. Commun. ACM Kuzman Ganchev, Yuriy Nevmyvaka, Michael J. Kearns, Jennifer Wortman Vaughan
2009	A	`conf`	Censored Exploration and the Dark Pool Problem. UAI Kuzman Ganchev, Michael J. Kearns, Yuriy Nevmyvaka, Jennifer Wortman Vaughan
2006	A*	`conf`	Reinforcement learning for optimized trade execution. ICML Yuriy Nevmyvaka, Yi Feng, Michael J. Kearns
2005	B	`conf`	Electronic Trading in Order-Driven Markets: Efficient Execution. CEC Yuriy Nevmyvaka, Michael J. Kearns, Amy Papandreou, Katia P. Sycara
2001	Misc	`conf`	A Practical Markov Chain Monte Carlo Approach to Decision Problems. FLAIRS Timothy Huang, Yuriy Nevmyvaka