Maksims Volkovs

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 38

Top Topics

User Engagement

Feature Importance

Top Venues

RecSys Challenge

Publications

Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh, Keyvan Golestan, Guangwei Yu, Maksims Volkovs, Anthony L. Caterini
Retrieval & Fine-Tuning for In-Context Tabular Models. CoRR (2024)
Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
Self-supervised Representation Learning from Random Data Projectors. ICLR (2024)
Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs
Self-supervised Representation Learning From Random Data Projectors. CoRR (2023)
Noël Vouitsis, Zhaoyan Liu, Satya Krishna Gorti, Valentin Villecroze, Jesse C. Cresswell, Guangwei Yu, Gabriel Loaiza-Ganem, Maksims Volkovs
Data-Efficient Multimodal Fusion on a Single GPU. CoRR (2023)
Kin Kwan Leung, Clayton Rooke, Jonathan Smith, Saba Zuberi, Maksims Volkovs
Temporal Dependencies in Feature Importance for Time Series Prediction. ICLR (2023)
Sajad Norouzi, Rasa Hosseinzadeh, Felipe Pérez, Maksims Volkovs
DiMS: Distilling Multiple Steps of Iterative Non-Autoregressive Transformers for Machine Translation. ACL (Findings) (2023)
Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan
DuETT: Dual Event Time Transformer for Electronic Health Records. MLHC (2023)
Yichao Lu, Maksims Volkovs
Robust User Engagement Modeling With Transformers and Self Supervision. RecSys Challenge (2023)
Linfeng Du, Ji Xin, Alex Labach, Saba Zuberi, Maksims Volkovs, Rahul G. Krishnan
MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting. CoRR (2023)
Alex Labach, Aslesha Pokhrel, Xiao Shi Huang, Saba Zuberi, Seung Eun Yi, Maksims Volkovs, Tomi Poutanen, Rahul G. Krishnan
DuETT: Dual Event Time Transformer for Electronic Health Records. CoRR (2023)
Xiao Shi Huang, Felipe Pérez, Maksims Volkovs
Improving Non-Autoregressive Translation Models Without Distillation. ICLR (2022)
Satya Krishna Gorti, Noël Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, Guang Wei Yu
X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. CoRR (2022)
Sajad Norouzi, Rasa Hosseinzadeh, Felipe Pérez, Maksims Volkovs
DiMS: Distilling Multiple Steps of Iterative Non-Autoregressive Transformers. CoRR (2022)
Zhaolin Gao, Zhaoyue Cheng, Felipe Pérez, Jianing Sun, Maksims Volkovs
MCL: Mixed-Centric Loss for Collaborative Filtering. WWW (2022)
Satya Krishna Gorti, Noël Vouitsis, Junwei Ma, Keyvan Golestan, Maksims Volkovs, Animesh Garg, Guangwei Yu
X-Pool: Cross-Modal Language-Video Attention for Text-Video Retrieval. CVPR (2022)
Maksims Volkovs, Felipe Pérez, Zhaoyue Cheng, Jianing Sun, Sajad Norouzi, Anson Wong, Pawel Jankiewicz, Barum Rho
User Engagement Modeling with Deep Learning and Language Models. RecSys Challenge (2021)
Shivam Kalra, Junfeng Wen, Jesse C. Cresswell, Maksims Volkovs, Hamid R. Tizhoosh
ProxyFL: Decentralized Federated Learning through Proxy Model Sharing. CoRR (2021)
Clayton Rooke, Jonathan Smith, Kin Kwan Leung, Maksims Volkovs, Saba Zuberi
Temporal Dependencies in Feature Importance for Time Series Predictions. CoRR (2021)
Junwei Ma, Satya Krishna Gorti, Maksims Volkovs, Guang Wei Yu
Weakly Supervised Action Selection Learning in Video. CoRR (2021)
Junwei Ma, Satya Krishna Gorti, Maksims Volkovs, Guang Wei Yu
Weakly Supervised Action Selection Learning in Video. CVPR (2021)
Mathieu Ravaut, Hamed Sadeghi, Kin Kwan Leung, Maksims Volkovs, Kathy Kornas, Vinyas Harish, Tristan Watson, Gary F. Lewis, Alanna Weisman, Tomi Poutanen, Laura C. Rosella
Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data. npj Digit. Medicine 4 (2021)
Yichao Lu, Himanshu Rai, Jason Chang, Boris Knyazev, Guang Wei Yu, Shashank Shekhar, Graham W. Taylor, Maksims Volkovs
Context-aware Scene Graph Generation with Seq2Seq Transformers. ICCV (2021)
Jianing Sun, Zhaoyue Cheng, Saba Zuberi, Felipe Pérez, Maksims Volkovs
HGCF: Hyperbolic Graph Convolution Networks for Collaborative Filtering. WWW (2021)
Xiao Shi Huang, Felipe Pérez, Jimmy Ba, Maksims Volkovs
Improving Transformer Optimization Through Better Initialization. ICML (2020)
Maksims Volkovs, Zhaoyue Cheng, Mathieu Ravaut, Hojin Yang, Kevin Shen, Jin Peng Zhou, Anson Wong, Saba Zuberi, Ivan Zhang, Nick Frosst, Helen Ngo, Carol Chen, Bharat Venkitesh, Stephen Gou, Aidan N. Gomez
Predicting Twitter Engagement With Deep Language Models. RecSys Challenge (2020)
Jin Peng Zhou, Zhaoyue Cheng, Felipe Pérez, Maksims Volkovs
TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations. RecSys (2020)
Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner, Himanshu Rai
Noise Contrastive Estimation for One-Class Collaborative Filtering. SIGIR (2019)
Yichao Lu, Cheng Chang, Himanshu Rai, Guang Wei Yu, Maksims Volkovs
Learning Effective Visual Relationship Detector on 1 GPU. CoRR (2019)
Junwei Ma, Satya Krishna Gorti, Maksims Volkovs, Ilya Stanevich, Guang Wei Yu
Cross-Class Relevance Learning for Temporal Concept Localization. CoRR (2019)
Chundi Liu, Guang Wei Yu, Maksims Volkovs, Cheng Chang, Himanshu Rai, Junwei Ma, Satya Krishna Gorti
Guided Similarity Separation for Image Retrieval. NeurIPS (2019)
Maksims Volkovs, Anson Wong, Zhaoyue Cheng, Felipe Pérez, Ilya Stanevich, Yichao Lu
Robust contextual models for in-session personalization. RecSys Challenge (2019)
Cheng Chang, Guang Wei Yu, Chundi Liu, Maksims Volkovs
Explore-Exploit Graph Traversal for Image Retrieval. CVPR (2019)
Mathieu Ravaut, Hamed Sadeghi, Kin Kwan Leung, Maksims Volkovs, Laura C. Rosella
Diabetes Mellitus Forecasting Using Population Health Data in Ontario, Canada. CoRR (2019)
Cheng Chang, Himanshu Rai, Satya Krishna Gorti, Junwei Ma, Chundi Liu, Guang Wei Yu, Maksims Volkovs
Semi-Supervised Exploration in Image Retrieval. CoRR (2019)
Maksims Volkovs, Himanshu Rai, Zhaoyue Cheng, Ga Wu, Yichao Lu, Scott Sanner
Two-stage Model for Automatic Playlist Continuation at Scale. RecSys Challenge (2018)
Ga Wu, Maksims Volkovs, Chee Loong Soon, Scott Sanner, Himanshu Rai
Noise Contrastive Estimation for Scalable Linear Models for One-Class Collaborative Filtering. CoRR (2018)
Chundi Liu, Shunan Zhao, Maksims Volkovs
Learning Document Embeddings With CNNs. CoRR (2017)
Maksims Volkovs, Guang Wei Yu, Tomi Poutanen
DropoutNet: Addressing Cold Start in Recommender Systems. NIPS (2017)
Maksims Volkovs
Two-Stage Approach to Item Recommendation from User Sessions. RecSys Challenge (2015)
Maksims Volkovs
Context Models For Web Search Personalization. CoRR (2015)
Maksims Volkovs, Guang Wei Yu
Effective Latent Models for Binary Feedback in Recommender Systems. SIGIR (2015)
Maksims Volkovs, Richard S. Zemel
New learning methods for supervised and unsupervised preference aggregation. J. Mach. Learn. Res. 15 (1) (2014)
Maksims Volkovs, Fei Chiang, Jaroslaw Szlichta, Renée J. Miller
Continuous data cleaning. ICDE (2014)
Maksims Volkovs, Richard S. Zemel
CRF framework for supervised preference aggregation. CIKM (2013)
Maksims Volkovs, Richard S. Zemel
Collaborative Ranking With 17 Parameters. NIPS (2012)
Maksims Volkovs, Hugo Larochelle, Richard S. Zemel
Learning to rank by aggregating expert preferences. CIKM (2012)
Maksims Volkovs, Richard S. Zemel
Efficient Sampling for Bipartite Matching Problems. NIPS (2012)
Maksims Volkovs, Richard S. Zemel
A flexible generative model for preference aggregation. WWW (2012)
Maksims Volkovs, Hugo Larochelle, Richard S. Zemel
Loss-sensitive Training of Probabilistic Conditional Random Fields CoRR (2011)
Krysta M. Svore, Maksims Volkovs, Christopher J. C. Burges
Learning to rank with multiple objective functions. WWW (2011)
Maksims Volkovs, Richard S. Zemel
BoltzRank: learning to maximize expected ranking gain. ICML (2009)
Chaitanya Mishra, Maksims Volkovs
ConEx: a system for monitoring queries. SIGMOD Conference (2007)