Laurens van der Maaten

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 87

Top Venues

CoRR

CVPR

ICPR

NeurIPS

Publications

Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert
Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds. CoRR (2024)
Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron B. Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky
Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset. CoRR (2023)
Vikram V. Ramaswamy, Sing Yu Lin, Dora Zhao, Aaron Adcock, Laurens van der Maaten, Deepti Ghadiyaram, Olga Russakovsky
GeoDE: a Geographically Diverse Evaluation Dataset for Object Recognition. NeurIPS (2023)
Xinlei Xu, Awni Y. Hannun, Laurens van der Maaten
Data Appraisal Without Data Sharing. AISTATS (2022)
Melissa Hall, Laurens van der Maaten, Laura Gustafson, Aaron Adcock
A Systematic Study of Bias Amplification. CoRR (2022)
Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
EIFFeL: Ensuring Integrity for Federated Learning. CCS (2022)
Karan Desai, Ishan Misra, Justin Johnson, Laurens van der Maaten
Scaling up Instance Segmentation using Approximately Localized Phrases. BMVC (2022)
Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
Measuring Data Leakage in Machine-Learning Models with Fisher Information (Extended Abstract). IJCAI (2022)
Mannat Singh, Laura Gustafson, Aaron Adcock, Vinicius de Freitas Reis, Bugra Gedik, Raj Prateek Kosaraju, Dhruv Mahajan, Ross B. Girshick, Piotr Dollár, Laurens van der Maaten
Revisiting Weakly Supervised Pre-Training of Visual Perception Models. CoRR (2022)
Antonio Ginart, Laurens van der Maaten, James Zou, Chuan Guo
Submix: Practical Private Prediction for Large-Scale Language Models. CoRR (2022)
Mannat Singh, Laura Gustafson, Aaron Adcock, Vinicius de Freitas Reis, Bugra Gedik, Raj Prateek Kosaraju, Dhruv Mahajan, Ross B. Girshick, Piotr Dollár, Laurens van der Maaten
Revisiting Weakly Supervised Pre-Training of Visual Perception Models. CVPR (2022)
Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
Convolutional Networks with Dense Connectivity. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten
Bounding Training Data Reconstruction in Private (Deep) Learning. ICML (2022)
Rohit Girdhar, Mannat Singh, Nikhila Ravi, Laurens van der Maaten, Armand Joulin, Ishan Misra
Omnivore: A Single Model for Many Visual Modalities. CVPR (2022)
Rohit Girdhar, Mannat Singh, Nikhila Ravi, Laurens van der Maaten, Armand Joulin, Ishan Misra
Omnivore: A Single Model for Many Visual Modalities. CoRR (2022)
Chuan Guo, Brian Karrer, Kamalika Chaudhuri, Laurens van der Maaten
Bounding Training Data Reconstruction in Private (Deep) Learning. CoRR (2022)
Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
EIFFeL: Ensuring Integrity for Federated Learning. CoRR (2021)
Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
Making Paper Reviewing Robust to Bid Manipulation Attacks. CoRR (2021)
Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten
CrypTen: Secure Multi-Party Computation Meets Machine Learning. CoRR (2021)
Brian Knott, Shobha Venkataraman, Awni Y. Hannun, Shubho Sengupta, Mark Ibrahim, Laurens van der Maaten
CrypTen: Secure Multi-Party Computation Meets Machine Learning. NeurIPS (2021)
Eltayeb Ahmed, Anton Bakhtin, Laurens van der Maaten, Rohit Girdhar
Physical Reasoning Using Dynamics-Aware Models. CoRR (2021)
Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
Measuring data leakage in machine-learning models with Fisher information. UAI (2021)
Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. CoRR (2021)
Ruihan Wu, Chuan Guo, Felix Wu, Rahul Kidambi, Laurens van der Maaten, Kilian Q. Weinberger
Making Paper Reviewing Robust to Bid Manipulation Attacks. ICML (2021)
Awni Y. Hannun, Chuan Guo, Laurens van der Maaten
Measuring Data Leakage in Machine-Learning Models with Fisher Information. CoRR (2021)
Ruihan Wu, Chuan Guo, Awni Y. Hannun, Laurens van der Maaten
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. NeurIPS (2021)
Mimee Xu, Laurens van der Maaten, Awni Y. Hannun
Data Appraisal Without Data Sharing. CoRR (2020)
Rohit Girdhar, Laura Gustafson, Aaron Adcock, Laurens van der Maaten
Forward Prediction for Physical Reasoning. CoRR (2020)
Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten
Certified Data Removal from Machine Learning Models. ICML (2020)
Ishan Misra, Laurens van der Maaten
Self-Supervised Learning of Pretext-Invariant Representations. CVPR (2020)
Laurens van der Maaten, Awni Y. Hannun
The Trade-Offs of Private Prediction. CoRR (2020)
Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
Convolutional Networks with Dense Connectivity. CoRR (2020)
Chuan Guo, Awni Y. Hannun, Brian Knott, Laurens van der Maaten, Mark Tygert, Ruiyu Zhu
Secure multiparty computations in floating-point arithmetic. CoRR (2020)
Awni Y. Hannun, Brian Knott, Shubho Sengupta, Laurens van der Maaten
Privacy-Preserving Contextual Bandits. CoRR (2019)
Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross B. Girshick
PHYRE: A New Benchmark for Physical Reasoning. CoRR (2019)
Abhimanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li, Dhruv Mahajan
Defense Against Adversarial Images Using Web-Scale Nearest-Neighbor Search. CVPR (2019)
Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten
Does Object Recognition Work for Everyone? CVPR Workshops (2019)
Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, Ross B. Girshick
PHYRE: A New Benchmark for Physical Reasoning. NeurIPS (2019)
Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Laurens van der Maaten
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. CoRR (2019)
Hexiang Hu, Ishan Misra, Laurens van der Maaten
Evaluating Text-to-Image Matching using Binary Image Selection (BISON). ICCV Workshops (2019)
Terrance DeVries, Ishan Misra, Changhan Wang, Laurens van der Maaten
Does Object Recognition Work for Everyone? CoRR (2019)
Ishan Misra, Laurens van der Maaten
Self-Supervised Learning of Pretext-Invariant Representations. CoRR (2019)
Hexiang Hu, Ishan Misra, Laurens van der Maaten
Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding. CoRR (2019)
Yin Cui, Zeqi Gu, Dhruv Mahajan, Laurens van der Maaten, Serge J. Belongie, Ser-Nam Lim
Measuring Dataset Granularity. CoRR (2019)
Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten
Certified Data Removal from Machine Learning Models. CoRR (2019)
Abhimanyu Dubey, Laurens van der Maaten, Zeki Yalniz, Yixuan Li, Dhruv Mahajan
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search. CoRR (2019)
Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark E. Campbell, Kilian Q. Weinberger
Anytime Stereo Image Depth Estimation on Mobile Devices. ICRA (2019)
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan L. Yuille, Kaiming He
Feature Denoising for Improving Adversarial Robustness. CVPR (2019)
Wenjie Pei, Hamdi Dibeklioglu, David M. J. Tax, Laurens van der Maaten
Multivariate Time-Series Classification Using the Hidden-Unit Logistic Model. IEEE Trans. Neural Networks Learn. Syst. 29 (4) (2018)
Benjamin Graham, Martin Engelcke, Laurens van der Maaten
3D Semantic Segmentation With Submanifold Sparse Convolutional Networks. CVPR (2018)
Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten
Separating Self-Expression and Visual Content in Hashtag Supervision. CVPR (2018)
Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger
CondenseNet: An Efficient DenseNet Using Learned Group Convolutions. CVPR (2018)
Cihang Xie, Yuxin Wu, Laurens van der Maaten, Alan L. Yuille, Kaiming He
Feature Denoising for Improving Adversarial Robustness. CoRR (2018)
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger
Multi-Scale Dense Networks for Resource Efficient Image Classification. ICLR (2018)
Taygun Kekeç, Laurens van der Maaten, David M. J. Tax
PAWE: Polysemy Aware Word Embeddings. ICISDM (2018)
Chuan Guo, Mayank Rana, Moustapha Cissé, Laurens van der Maaten
Countering Adversarial Images using Input Transformations. ICLR (Poster) (2018)
Yan Wang, Zihang Lai, Gao Huang, Brian H. Wang, Laurens van der Maaten, Mark Campbell, Kilian Q. Weinberger
Anytime Stereo Image Depth Estimation on Mobile Devices. CoRR (2018)
Dhruv Mahajan, Ross B. Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, Laurens van der Maaten
Exploring the Limits of Weakly Supervised Pretraining. ECCV (2) (2018)
Dhruv Mahajan, Ross B. Girshick, Vignesh Ramanathan, Kaiming He, Manohar Paluri, Yixuan Li, Ashwin Bharambe, Laurens van der Maaten
Exploring the Limits of Weakly Supervised Pretraining. CoRR (2018)
Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
Learning by Asking Questions. CVPR (2018)
Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten, Thomas Höllt, Elmar Eisemann, Anna Vilanova
Approximated and User Steerable tSNE for Progressive Visual Analytics. IEEE Trans. Vis. Comput. Graph. 23 (7) (2017)
Ang Li, Allan Jabri, Armand Joulin, Laurens van der Maaten
Learning Visual N-Grams from Web Data. ICCV (2017)
Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
Densely Connected Convolutional Networks. CVPR (2017)
Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger
Memory-Efficient Implementation of DenseNets. CoRR (2017)
Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger
CondenseNet: An Efficient DenseNet using Learned Group Convolutions. CoRR (2017)
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
Inferring and Executing Programs for Visual Reasoning. CoRR (2017)
Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten
Separating Self-Expression and Visual Content in Hashtag Supervision. CoRR (2017)
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Judy Hoffman, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
Inferring and Executing Programs for Visual Reasoning. ICCV (2017)
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning. CVPR (2017)
Chuan Guo, Mayank Rana, Moustapha Cissé, Laurens van der Maaten
Countering Adversarial Images using Input Transformations. CoRR (2017)
Benjamin Graham, Laurens van der Maaten
Submanifold Sparse Convolutional Networks. CoRR (2017)
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger
Multi-Scale Dense Convolutional Networks for Efficient Prediction. CoRR (2017)
Benjamin Graham, Martin Engelcke, Laurens van der Maaten
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks. CoRR (2017)
Ishan Misra, Ross B. Girshick, Rob Fergus, Martial Hebert, Abhinav Gupta, Laurens van der Maaten
Learning by Asking Questions. CoRR (2017)
Allan Jabri, Armand Joulin, Laurens van der Maaten
Revisiting Visual Question Answering Baselines. ECCV (8) (2016)
Kevin van Hecke, Guido de Croon, Laurens van der Maaten, Daniel Hennes, Dario Izzo
Persistent self-supervised learning principle: from stereo to monocular vision for obstacle avoidance. CoRR (2016)
Allan Jabri, Armand Joulin, Laurens van der Maaten
Revisiting Visual Question Answering Baselines. CoRR (2016)
Armand Joulin, Laurens van der Maaten, Allan Jabri, Nicolas Vasilache
Learning Visual Features from Large Weakly Supervised Data. ECCV (7) (2016)
Ang Li, Allan Jabri, Armand Joulin, Laurens van der Maaten
Learning Visual N-Grams from Web Data. CoRR (2016)
Wenjie Pei, David M. J. Tax, Laurens van der Maaten
Modeling Time Series Similarity with Siamese Recurrent Networks. CoRR (2016)
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, Ross B. Girshick
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning. CoRR (2016)
Michaël Aupetit, Laurens van der Maaten
Introduction to the special issue on visual analytics using multidimensional projections. Neurocomputing 150 (2015)
Armand Joulin, Laurens van der Maaten, Allan Jabri, Nicolas Vasilache
Learning Visual Features from Large Weakly Supervised Data. CoRR (2015)
Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten, Thomas Höllt, Elmar Eisemann, Anna Vilanova
Approximated and User Steerable tSNE for Progressive Visual Analytics. CoRR (2015)
Laurens van der Maaten, Robert G. Erdmann
Automatic Thread-Level Canvas Analysis: A machine-learning approach to analyzing the canvas of paintings. IEEE Signal Process. Mag. 32 (4) (2015)
Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
Adaptive stereo similarity fusion using confidence measures. Comput. Vis. Image Underst. 135 (2015)
Wenjie Pei, Hamdi Dibeklioglu, David M. J. Tax, Laurens van der Maaten
Time Series Classification using the Hidden-Unit Logistic Model. CoRR (2015)
Laurens van der Maaten
Accelerating t-SNE using tree-based algorithms. J. Mach. Learn. Res. 15 (1) (2014)
Lu Zhang, Laurens van der Maaten
Improving Object Tracking by Adapting Detectors. ICPR (2014)
Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
Hybrid Kinect Depth Map Refinement for Transparent Objects. ICPR (2014)
Lu Zhang, Hamdi Dibeklioglu, Laurens van der Maaten
Speeding Up Tracking by Ignoring Features. CVPR (2014)
Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
Marginalizing Corrupted Features. CoRR (2014)
Yuanhao Guo, Hamdi Dibeklioglu, Laurens van der Maaten
Graph-Based Kinship Recognition. ICPR (2014)
Lu Zhang, Laurens van der Maaten
Preserving Structure in Model-Free Tracking. IEEE Trans. Pattern Anal. Mach. Intell. 36 (4) (2014)
Gorkem Saygili, Laurens van der Maaten, Emile A. Hendriks
Stereo Similarity Metric Fusion Using Stereo Confidence. ICPR (2014)
Lu Zhang, Hamdi Dibeklioglu, Laurens van der Maaten
On Fast Trackers that are Robust to Partial Occlusions. CVPR Workshops (2014)
Laurens van der Maaten
Barnes-Hut-SNE ICLR (2013)
Lu Zhang, Laurens van der Maaten
Structure Preserving Object Tracking. CVPR (2013)
Joshua M. Lewis, Virginia R. de Sa, Laurens van der Maaten
Divvy: fast and intuitive exploratory data analysis. J. Mach. Learn. Res. 14 (1) (2013)
Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger
Learning with Marginalized Corrupted Features. ICML (1) (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Laurens van der Maaten