Andreas Veit

According to our database, Andreas Veit authored at least 41 papers between 2013 and 2024.

Collaborative distances:

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

2024

Efficient Document Ranking with Learnable Late Interactions.

Ziwei Ji, Himanshu Jain, Andreas Veit, Sashank J. Reddi, Sadeep Jayasumana, Ankit Singh Rawat, Aditya Krishna Menon, Felix Yu, Sanjiv Kumar

CoRR, 2024

Rethinking FID: Towards a Better Evaluation Metric for Image Generation.

Sadeep Jayasumana, Srikumar Ramalingam, Andreas Veit, Daniel Glasner, Ayan Chakrabarti, Sanjiv Kumar

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

MarkovGen: Structured Prediction for Efficient Text-to-Image Generation.

Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

SPEGTI: Structured Prediction for Efficient Generative Text-to-Image Models.

Sadeep Jayasumana, Daniel Glasner, Srikumar Ramalingam, Andreas Veit, Ayan Chakrabarti, Sanjiv Kumar

CoRR, 2023

Teacher Guided Training: An Efficient Framework for Knowledge Transfer.

Manzil Zaheer, Ankit Singh Rawat, Seungyeon Kim, Chong You, Himanshu Jain, Andreas Veit, Rob Fergus, Sanjiv Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Large Language Models with Controllable Working Memory.

Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

When does mixup promote local linearity in learned representations?

Arslan Chaudhry, Aditya Krishna Menon, Andreas Veit, Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar

CoRR, 2022

2021

Leveraging redundancy in attention with Reuse Transformers.

Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar

CoRR, 2021

Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation.

Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain, Sanjiv Kumar, Michal Lukasik, Andreas Veit

CoRR, 2021

On the Reproducibility of Neural Network Predictions.

Srinadh Bhojanapalli, Kimberly Wilber, Andreas Veit, Ankit Singh Rawat, Seungyeon Kim, Aditya Krishna Menon, Sanjiv Kumar

CoRR, 2021

Coping with Label Shift via Distributionally Robust Optimisation.

Jingzhao Zhang, Aditya Krishna Menon, Andreas Veit, Srinadh Bhojanapalli, Sanjiv Kumar, Suvrit Sra

Proceedings of the 9th International Conference on Learning Representations, 2021

Long-tail learning via logit adjustment.

Aditya Krishna Menon, Sadeep Jayasumana, Ankit Singh Rawat, Himanshu Jain, Andreas Veit, Sanjiv Kumar

Proceedings of the 9th International Conference on Learning Representations, 2021

Understanding Robustness of Transformers for Image Classification.

Srinadh Bhojanapalli, Ayan Chakrabarti, Daniel Glasner, Daliang Li, Thomas Unterthiner, Andreas Veit

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

RankDistil: Knowledge Distillation for Ranking.

Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Convolutional Networks with Adaptive Inference Graphs.

Andreas Veit, Serge J. Belongie

Int. J. Comput. Vis., 2020

Improving Calibration in Deep Metric Learning With Cross-Example Softmax.

Andreas Veit, Kimberly Wilber

CoRR, 2020

Doubly-stochastic mining for heterogeneous retrieval.

Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar

CoRR, 2020

Why are Adaptive Methods Good for Attention Models?

Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

How To Backdoor Federated Learning.

Eugene Bagdasaryan, Andreas Veit, Yiqing Hua, Deborah Estrin, Vitaly Shmatikov

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Why ADAM Beats SGD for Attention Models.

Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J. Reddi, Sanjiv Kumar, Suvrit Sra

CoRR, 2019

2018

Semantic Segmentation with Scarce Data.

Isay Katsman, Rohun Tripathi, Andreas Veit, Serge J. Belongie

CoRR, 2018

Separating Self-Expression and Visual Content in Hashtag Supervision.

Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning to Evaluate Image Captioning.

Yin Cui, Guandao Yang, Andreas Veit, Xun Huang, Serge J. Belongie

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Convolutional Networks with Adaptive Computation Graphs.

Andreas Veit, Serge J. Belongie

CoRR, 2017

Deep Learning is Robust to Massive Label Noise.

David Rolnick, Andreas Veit, Serge J. Belongie, Nir Shavit

CoRR, 2017

Crowd Research: Open and Scalable University Laboratories.

Rajan Vaish, Snehalkumar (Neil) S. Gaikwad, Geza Kovacs, Andreas Veit, Ranjay Krishna, Imanol Arrieta Ibarra, Camelia Simoiu, Michael J. Wilber, Serge J. Belongie, Sharad Goel, James Davis, Michael S. Bernstein

Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology, 2017

ICDAR2017 Robust Reading Challenge on COCO-Text.

Raul Gomez, Baoguang Shi, Lluis Gomez-Bigorda, Lukás Neumann, Andreas Veit, Jiri Matas, Serge J. Belongie, Dimosthenis Karatzas

Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017

Conditional Similarity Networks.

Andreas Veit, Serge J. Belongie, Theofanis Karaletsos

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Learning from Noisy Large-Scale Datasets with Minimal Supervision.

Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge J. Belongie

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Residual Networks are Exponential Ensembles of Relatively Shallow Networks.

Andreas Veit, Michael J. Wilber, Serge J. Belongie

CoRR, 2016

COCO-Text: Dataset and Benchmark for Text Detection and Recognition in Natural Images.

Andreas Veit, Tomas Matera, Lukás Neumann, Jiri Matas, Serge J. Belongie

CoRR, 2016

Disentangling Nonlinear Perceptual Embeddings With Multi-Query Triplet Networks.

Andreas Veit, Serge J. Belongie, Theofanis Karaletsos

CoRR, 2016

Residual Networks Behave Like Ensembles of Relatively Shallow Networks.

Andreas Veit, Michael J. Wilber, Serge J. Belongie

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning to Detect and Match Keypoints with Deep Architectures.

Hani Altwaijry, Andreas Veit, Serge J. Belongie

Proceedings of the British Machine Vision Conference 2016, 2016

2015

On Optimizing Human-Machine Task Assignments.

Andreas Veit, Michael J. Wilber, Rajan Vaish, Serge J. Belongie, James Davis, Vishal Anand, Anshu Aviral, Prithvijit Chakrabarty, Yash Chandak, Sidharth Chaturvedi, Chinmaya Devaraj, Ankit Dhall, Utkarsh Dwivedi, Sanket Gupte, Sharath N. Sridhar, Karthik Paga, Anuj Pahuja, Aditya Raisinghani, Ayush Sharma, Shweta Sharma, Darpana Sinha, Nisarg Thakkar, K. Bala Vignesh, Utkarsh Verma, Kanniganti Abhishek, Amod Agrawal, Arya Aishwarya, Aurgho Bhattacharjee, Sarveshwaran Dhanasekar, Venkata Karthik Gullapalli, Shuchita Gupta, Chandana G, Kinjal Jain, Simran Kapur, Meghana Kasula, Shashi Kumar, Parth Kundaliya, Utkarsh Mathur, Alankrit Mishra, Aayush Mudgal, Aditya Nadimpalli, Munakala Sree Nihit, Akanksha Periwal, Ayush Sagar, Ayush Shah, Vikas Sharma, Yashovardhan Sharma, Faizal Siddiqui, Virender Singh, Abhinav S., Pradyumna Tambwekar, Rashida Taskin, Ankit Tripathi, Anurag D. Yadav

CoRR, 2015

Multi-agent device-level modeling framework for demand scheduling.

Andreas Veit, Hans-Arno Jacobsen

Proceedings of the 2015 IEEE International Conference on Smart Grid Communications, 2015

MDSM: Generalized multiagent coordination for demand side management.

Andreas Veit

Proceedings of the 2015 IEEE International Conference on Smart Grid Communications, 2015

Learning Visual Clothing Style with Heterogeneous Dyadic Co-Occurrences.

Andreas Veit, Balazs Kovacs, Sean Bell, Julian J. McAuley, Kavita Bala, Serge J. Belongie

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Demand Side Energy Management via Multiagent Coordination in Consumer Cooperatives.

Andreas Veit, Ying Xu, Ronghuo Zheng, Nilanjan Chakraborty, Katia P. Sycara

J. Artif. Intell. Res., 2014

Household electricity demand forecasting: benchmarking state-of-the-art methods.

Andreas Veit, Christoph Goebel, Rohit Tidke, Christoph Doblander, Hans-Arno Jacobsen

Proceedings of the Fifth International Conference on Future Energy Systems, 2014

2013

Multiagent Coordination for Energy Consumption Scheduling in Consumer Cooperatives.

Andreas Veit, Ying Xu, Ronghuo Zheng, Nilanjan Chakraborty, Katia P. Sycara

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013