Dima Kuzmin

According to our database, Dima Kuzmin authored at least 14 papers between 2005 and 2024.

Collaborative distances:

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

2024

User Embedding Model for Personalized Language Prompting.

Sumanth Doddapaneni, Krishna Sayana, Ambarish Jash, Sukhdeep S. Sodhi, Dima Kuzmin

CoRR, 2024

V2Meow: Meowing to the Visual Beat via Video-to-Music Generation.

Kun Su, Judith Yue Li, Qingqing Huang, Dima Kuzmin, Joonseok Lee, Chris Donahue, Fei Sha, Aren Jansen, Yu Wang, Mauro Verzetti, Timo I. Denk

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

V2Meow: Meowing to the Visual Beat via Music Generation.

Kun Su, Judith Yue Li, Qingqing Huang, Dima Kuzmin, Joonseok Lee, Chris Donahue, Fei Sha, Aren Jansen, Yu Wang, Mauro Verzetti, Timo I. Denk

CoRR, 2023

Multi-Task End-to-End Training Improves Conversational Recommendation.

Naveen Ram, Dima Kuzmin, Ellie Ka In Chio, Moustafa Farid Alzantot, Santiago Ontañón, Ambarish Jash, Judith Yue Li

CoRR, 2023

MAQA: A Multimodal QA Benchmark for Negation.

Judith Yue Li, Aren Jansen, Qingqing Huang, Joonseok Lee, Ravi Ganti, Dima Kuzmin

CoRR, 2023

2021

Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries.

Sukhdeep S. Sodhi, Ellie Ka In Chio, Ambarish Jash, Santiago Ontañón, Ajit Apte, Ankit Kumar, Ayooluwakunmi Jeje, Dima Kuzmin, Harry Fung, Heng-Tze Cheng, Jon Effrat, Tarush Bali, Nitin Jindal, Pei Cao, Sarvjeet Singh, Senqiang Zhou, Tameen Khan, Amol Wankhede, Moustafa Alzantot, Allen Wu, Tushar Chandra

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval.

Tao Wu, Ellie Ka In Chio, Heng-Tze Cheng, Yu Du, Steffen Rendle, Dima Kuzmin, Ritesh Agarwal, Li Zhang, John R. Anderson, Sarvjeet Singh, Tushar Chandra, Ed H. Chi, Wen Li, Ankit Kumar, Xiang Ma, Alex Soares, Nitin Jindal, Pei Cao

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2012

Online variance minimization.

Manfred K. Warmuth, Dima Kuzmin

Mach. Learn., 2012

2010

Bayesian generalized probability calculus for density matrices.

Manfred K. Warmuth, Dima Kuzmin

Mach. Learn., 2010

2007

Unlabeled Compression Schemes for Maximum Classes.

Dima Kuzmin, Manfred K. Warmuth

J. Mach. Learn. Res., 2007

Online kernel PCA with entropic matrix updates.

Dima Kuzmin, Manfred K. Warmuth

Proceedings of the Machine Learning, 2007

2006

A Bayesian Probability Calculus for Density Matrices.

Manfred K. Warmuth, Dima Kuzmin

Proceedings of the UAI '06, 2006

Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension.

Manfred K. Warmuth, Dima Kuzmin

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

Optimum Follow the Leader Algorithm.

Dima Kuzmin, Manfred K. Warmuth

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005