Sadeep Jayasumana

37 papers A* 10A 2C 1Misc 1Journal 21Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Efficient Document Ranking with Learnable Late Interactions. CoRR Ziwei Ji, Himanshu Jain, Andreas Veit, Sashank J. Reddi, Sadeep Jayasumana, Ankit Singh Rawat, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
2024	J	`jnl`	LatentCRF: Continuous CRF for Efficient Latent Diffusion. CoRR Kanchana Ranasinghe, Sadeep Jayasumana, Andreas Veit, Ayan Chakrabarti, Daniel Glasner, Michael S. Ryoo, Srikumar Ramalingam, Sanjiv Kumar
2024	A*	`conf`	MarkovGen: Structured Prediction for Efficient Text-to-Image Generation. CVPR Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar
2024	A*	`conf`	Rethinking FID: Towards a Better Evaluation Metric for Image Generation. CVPR Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar
2024	J	`jnl`	Rethinking FID: Towards a Better Evaluation Metric for Image Generation. CoRR Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar
2024	A*	`conf`	USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval. ICML Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Wittawat Jitkrittum, Veeranjaneyulu Sadhanala, Sadeep Jayasumana, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
2023	J	`jnl`	EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval. CoRR Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer, Sadeep Jayasumana, Veeranjaneyulu Sadhanala, Wittawat Jitkrittum, Aditya Krishna Menon, Rob Fergus, Sanjiv Kumar
2023	J	`jnl`	SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models. CoRR Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar
2022	A*	`conf`	In defense of dual-encoders for neural ranking. ICML Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar
2022	J	`jnl`	When does mixup promote local linearity in learned representations? CoRR Arslan Chaudhry, Aditya Krishna Menon, Andreas Veit, Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar
2021	J	`jnl`	Balancing Constraints and Submodularity in Data Subset Selection. CoRR Srikumar Ramalingam, Daniel Glasner, Kaushal Patel, Raviteja Vemulapalli, Sadeep Jayasumana, Sanjiv Kumar
2021	J	`jnl`	Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces. CoRR Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2021	A*	`conf`	Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. ICML Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
2021	A*	`conf`	Long-tail learning via logit adjustment. ICLR Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
2020	A	`conf`	Bipartite Conditional Random Fields for Panoptic Segmentation. BMVC Sadeep Jayasumana, Kanchana Ranasinghe, Sahan Liyanaarachchi, Mayuka Jayawardhana, Harsha Ranasinghe, Sina Samangooei
2020	J	`jnl`	Kernelized Classification in Deep Networks. CoRR Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar
2020	J	`jnl`	Long-tail learning via logit adjustment. CoRR Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar
2019	J	`jnl`	Bipartite Conditional Random Fields for Panoptic Segmentation. CoRR Sadeep Jayasumana, Kanchana Ranasinghe, Mayuka Jayawardhana, Sahan Liyanaarachchi, Harsha Ranasinghe
2018	J	`jnl`	Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction. IEEE Signal Process. Mag. Anurag Arnab, Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Måns Larsson, Alexander Kirillov, Bogdan Savchynskyy, Carsten Rother, Fredrik Kahl, Philip H. S. Torr
2016	—	`conf`	Higher Order Conditional Random Fields in Deep Neural Networks. ECCV (2) Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr
2015	A*	`conf`	Conditional Random Fields as Recurrent Neural Networks. ICCV Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr
2015	J	`jnl`	Conditional Random Fields as Recurrent Neural Networks. CoRR Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr
2015	J	`jnl`	Higher Order Potentials in End-to-End Trainable Conditional Random Fields. CoRR Anurag Arnab, Sadeep Jayasumana, Shuai Zheng, Philip H. S. Torr
2015	J	`jnl`	Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels. IEEE Trans. Pattern Anal. Mach. Intell. Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2015	A	`conf`	Prototypical Priors: From Improving Classification to Zero-Shot Learning. BMVC Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip H. S. Torr
2015	J	`jnl`	Prototypical Priors: From Improving Classification to Zero-Shot Learning. CoRR Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip H. S. Torr
2014	J	`jnl`	A Framework for Shape Analysis via Hilbert Space Embedding. CoRR Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2014	—	`conf`	Expanding the Family of Grassmannian Kernels: An Embedding Perspective. ECCV (7) Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Sadeep Jayasumana, Richard I. Hartley, Hongdong Li
2014	J	`jnl`	Expanding the Family of Grassmannian Kernels: An Embedding Perspective. CoRR Mehrtash Tafazzoli Harandi, Mathieu Salzmann, Sadeep Jayasumana, Richard I. Hartley, Hongdong Li
2014	J	`jnl`	Kernel Methods on Riemannian Manifolds with Gaussian RBF Kernels. CoRR Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2014	J	`jnl`	Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices. CoRR Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2014	J	`jnl`	Optimizing Over Radial Kernels on Compact Manifolds. CoRR Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2014	A*	`conf`	Optimizing over Radial Kernels on Compact Manifolds. CVPR Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2013	A*	`conf`	A Framework for Shape Analysis via Hilbert Space Embedding. ICCV Sadeep Jayasumana, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2013	Misc	`conf`	Combining Multiple Manifold-Valued Descriptors for Improved Object Recognition. DICTA Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi
2013	C	`conf`	Improved Server Architecture for Highly Efficient Message Mediation. iiWAS Hiranya Jayathilaka, Pradeep R. Fernando, Paul Fremantle, Kasun Indrasiri, Dushan Abeyruwan, Supun Kamburugamuve, Sadeep Jayasumana, Sanjiva Weerawarana, Srinath Perera
2013	A*	`conf`	Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices. CVPR Sadeep Jayasumana, Richard I. Hartley, Mathieu Salzmann, Hongdong Li, Mehrtash Tafazzoli Harandi