Ajanthan, Thalaiyasingam

27 publications

ICLRW 2025 Beyond Top-K: Structured Sparsification for Compression in Pipeline Parallel Sameera Ramasinghe, Thalaiyasingam Ajanthan, Gil Avraham, Yan Zuo, Alexander Long

ICLRW 2025 Exploring Asynchronism in SWARM Parallelism Yan Zuo, Gil Avraham, Thalaiyasingam Ajanthan, Sameera Ramasinghe, Alexander Long

ICCV 2025 Learning Visual Hierarchies in Hyperbolic Space for Image Retrieval Ziwei Wang, Sameera Ramasinghe, Chenchen Xu, Julien Monteil, Loris Bazzani, Thalaiyasingam Ajanthan

NeurIPS 2025 Mixtures of Subspaces for Bandwidth Efficient Context Parallel Training Sameera Ramasinghe, Thalaiyasingam Ajanthan, Hadi Mohaghegh Dolatabadi, Gil Avraham, Violetta Shevchenko, Yan Zuo, Chamin P Hewa Koneputugodage, Alexander Long

ICLRW 2025 Momentum Look-Ahead for Asynchronous Distributed Low-Communication Training Thalaiyasingam Ajanthan, Sameera Ramasinghe, Gil Avraham, Yan Zuo, Alexander Long

ICML 2025 Nesterov Method for Asynchronous Pipeline Parallel Optimization Thalaiyasingam Ajanthan, Sameera Ramasinghe, Yan Zuo, Gil Avraham, Alexander Long

NeurIPS 2025 Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings Evan Markou, Thalaiyasingam Ajanthan, Stephen Gould

NeurIPS 2025 Subspace Networks: Scaling Decentralized Training with Communication-Efficient Model Parallelism Sameera Ramasinghe, Thalaiyasingam Ajanthan, Gil Avraham, Yan Zuo, Alexander Long

NeurIPS 2025 Unextractable Protocol Models: Collaborative Training and Inference Without Weight Materialization Alexander Long, Chamin P Hewa Koneputugodage, Thalaiyasingam Ajanthan, Yan Zuo, Gil Avraham, Violetta Shevchenko, Hadi Mohaghegh Dolatabadi, Sameera Ramasinghe

NeurIPS 2024 Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame Evan Markou, Thalaiyasingam Ajanthan, Stephen Gould

ICLRW 2023 Modality-Aware Adaptation of Contrastive Language-Image Models Alexander Long, Thalaiyasingam Ajanthan, Anton van den Hengel

ICCV 2023 Semi-Supervised Semantic Segmentation Under Label Noise via Diverse Learning Groups Peixia Li, Pulak Purkait, Thalaiyasingam Ajanthan, Majid Abdolshah, Ravi Garg, Hisham Husain, Chenchen Xu, Stephen Gould, Wanli Ouyang, Anton van den Hengel

WACV 2022 Few-Shot Weakly-Supervised Object Detection via Directional Statistics Amirreza Shaban, Amir Rahimi, Thalaiyasingam Ajanthan, Byron Boots, Richard Hartley

AAAI 2022 Improved Gradient-Based Adversarial Attacks for Quantized Networks Kartik Gupta, Thalaiyasingam Ajanthan

CVPR 2022 Retrieval Augmented Classification for Long-Tail Visual Recognition Alexander Long, Wei Yin, Thalaiyasingam Ajanthan, Vu Nguyen, Pulak Purkait, Ravi Garg, Alan Blair, Chunhua Shen, Anton van den Hengel

AISTATS 2021 Mirror Descent View for Neural Network Quantization Thalaiyasingam Ajanthan, Kartik Gupta, Philip Torr, Richad Hartley, Puneet Dokania

ICLR 2021 Calibration of Neural Networks Using Splines Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley

ICLR 2021 Understanding the Effects of Data Parallelism and Sparsity on Neural Network Training Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr, Martin Jaggi

ICLR 2020 A Signal Propagation Perspective for Pruning Neural Networks at Initialization Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, Philip H. S. Torr

ECCV 2020 Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization Amir Rahimi, Amirreza Shaban, Thalaiyasingam Ajanthan, Richard Hartley, Byron Boots

WACV 2019 A Conditional Deep Generative Model of People in Natural Images Rodrigo Andrade de Bem, Arnab Ghosh, Adnane Boukhayma, Thalaiyasingam Ajanthan, N. Siddharth, Philip H. S. Torr

ICLR 2019 Snip: Single-Shot Network Pruning Based on Connection Sensitivity Namhoon Lee, Thalaiyasingam Ajanthan, Philip Torr

ECCVW 2018 A Semi-Supervised Deep Generative Model for Human Body Analysis Rodrigo Andrade de Bem, Arnab Ghosh, Thalaiyasingam Ajanthan, Ondrej Miksik, N. Siddharth, Philip H. S. Torr

ECCV 2018 Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence Arslan Chaudhry, Puneet K. Dokania, Thalaiyasingam Ajanthan, Philip H. S. Torr

CVPR 2017 Efficient Linear Programming for Dense CRFs Thalaiyasingam Ajanthan, Alban Desmaison, Rudy Bunel, Mathieu Salzmann, Philip H. S. Torr, M. Pawan Kumar

CVPR 2016 Memory Efficient Max Flow for Multi-Label Submodular MRFs Thalaiyasingam Ajanthan, Richard Hartley, Mathieu Salzmann

CVPR 2015 Iteratively Reweighted Graph Cut for Multi-Label MRFs with Non-Convex Priors Thalaiyasingam Ajanthan, Richard Hartley, Mathieu Salzmann, Hongdong Li