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ORCIDKilian Q. Weinberger
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- affiliation: Department of Computer Science and Engineering, Washington University in St. Louis
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2020 – today
- 2020
[c84]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CVPR 2020: 5880-5889- [c83]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in the USA: Making 3D Object Detectors Generalize. CVPR 2020: 11710-11720 - [c82]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. ICLR 2020 - [c81]Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi:
BERTScore: Evaluating Text Generation with BERT. ICLR 2020 - [i57]Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger:
Convolutional Networks with Dense Connectivity. CoRR abs/2001.02394 (2020) - [i56]Geoff Pleiss, Tianyi Zhang, Ethan R. Elenberg, Kilian Q. Weinberger:
Identifying Mislabeled Data using the Area Under the Margin Ranking. CoRR abs/2001.10528 (2020) - [i55]Wei-Lun Chao, Han-Jia Ye, De-Chuan Zhan, Mark E. Campbell, Kilian Q. Weinberger:
Revisiting Meta-Learning as Supervised Learning. CoRR abs/2002.00573 (2020) - [i54]Chuan Guo, Ruihan Wu, Kilian Q. Weinberger:
TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks. CoRR abs/2002.10078 (2020) - [i53]Boyi Li, Felix Wu, Ser-Nam Lim, Serge J. Belongie, Kilian Q. Weinberger:
On Feature Normalization and Data Augmentation. CoRR abs/2002.11102 (2020) - [i52]Rui Qian, Divyansh Garg, Yan Wang, Yurong You, Serge J. Belongie, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection. CoRR abs/2004.03080 (2020) - [i51]Yan Wang, Xiangyu Chen, Yurong You, Li Erran Li, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Train in Germany, Test in The USA: Making 3D Object Detectors Generalize. CoRR abs/2005.08139 (2020) - [i50]Tianyi Zhang, Felix Wu, Arzoo Katiyar, Kilian Q. Weinberger, Yoav Artzi:
Revisiting Few-sample BERT Fine-tuning. CoRR abs/2006.05987 (2020) - [i49]Divyansh Garg, Yan Wang, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger, Wei-Lun Chao:
Wasserstein Distances for Stereo Disparity Estimation. CoRR abs/2007.03085 (2020) - [i48]Luyu Yang, Yan Wang, Mingfei Gao, Abhinav Shrivastava, Kilian Q. Weinberger, Wei-Lun Chao, Ser-Nam Lim:
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation. CoRR abs/2007.12684 (2020)
2010 – 2019
- 2019
- [j10]Brian H. Wang
, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. IEEE Robotics Autom. Lett. 4(3): 2902-2909 (2019) - [c80]Carlos Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Mark E. Campbell:
Vision-only 3D Tracking for Self-Driving Cars. CASE 2019: 1029-1034 - [c79]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark E. Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CVPR 2019: 8445-8453 - [c78]Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger:
Simple Black-box Adversarial Attacks. ICML 2019: 2484-2493 - [c77]Felix Wu, Amauri H. Souza Jr., Tianyi Zhang, Christopher Fifty, Tao Yu, Kilian Q. Weinberger:
Simplifying Graph Convolutional Networks. ICML 2019: 6861-6871 - [c76]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: 5893-5900 - [c75]Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie:
Positional Normalization. NeurIPS 2019: 1620-1632 - [c74]Shengyuan Hu, Tao Yu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. NeurIPS 2019: 1633-1644 - [c73]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. NeurIPS 2019: 14622-14632 - [c72]Chuan Guo, Jared S. Frank, Kilian Q. Weinberger:
Low Frequency Adversarial Perturbation. UAI 2019: 411 - [i47]Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng:
Gradient Boosted Feature Selection. CoRR abs/1901.04055 (2019) - [i46]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Alice X. Zheng:
Gradient Regularized Budgeted Boosting. CoRR abs/1901.04065 (2019) - [i45]Felix Wu, Tianyi Zhang, Amauri H. Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger:
Simplifying Graph Convolutional Networks. CoRR abs/1902.07153 (2019) - [i44]Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger:
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD. CoRR abs/1902.11291 (2019) - [i43]Ke Alexander Wang, Geoff Pleiss, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger, Andrew Gordon Wilson:
Exact Gaussian Processes on a Million Data Points. CoRR abs/1903.08114 (2019) - [i42]Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, Yoav Artzi:
BERTScore: Evaluating Text Generation with BERT. CoRR abs/1904.09675 (2019) - [i41]Chuan Guo, Jacob R. Gardner, Yurong You, Andrew Gordon Wilson, Kilian Q. Weinberger:
Simple Black-box Adversarial Attacks. CoRR abs/1905.07121 (2019) - [i40]Yurong You, Yan Wang, Wei-Lun Chao, Divyansh Garg, Geoff Pleiss, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving. CoRR abs/1906.06310 (2019) - [i39]Boyi Li, Felix Wu, Kilian Q. Weinberger, Serge J. Belongie:
Positional Normalization. CoRR abs/1907.04312 (2019) - [i38]Felix Wu, Boyi Li, Lequn Wang, Ni Lao, John Blitzer, Kilian Q. Weinberger:
Integrated Triaging for Fast Reading Comprehension. CoRR abs/1909.13128 (2019) - [i37]Tao Yu, Shengyuan Hu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger:
A New Defense Against Adversarial Images: Turning a Weakness into a Strength. CoRR abs/1910.07629 (2019) - [i36]Brian H. Wang, Wei-Lun Chao, Yan Wang, Bharath Hariharan, Kilian Q. Weinberger, Mark E. Campbell:
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images. CoRR abs/1910.13955 (2019) - [i35]Yan Wang, Wei-Lun Chao, Kilian Q. Weinberger, Laurens van der Maaten:
SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning. CoRR abs/1911.04623 (2019) - 2018
- [j9]Sheila A. McIlraith, Kilian Q. Weinberger, G. Michael Youngblood, Karen L. Myers, Eric Eaton, Michael Wollowski:
A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium. AI Mag. 39(4): 3-16 (2018) - [j8]Xilun Chen, Yu Sun, Ben Athiwaratkun, Claire Cardie, Kilian Q. Weinberger:
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. Trans. Assoc. Comput. Linguistics 6: 557-570 (2018) - [c71]Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson:
Product Kernel Interpolation for Scalable Gaussian Processes. AISTATS 2018: 1407-1416 - [c70]Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger:
CondenseNet: An Efficient DenseNet Using Learned Group Convolutions. CVPR 2018: 2752-2761 - [c69]Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger:
Resource Aware Person Re-Identification Across Multiple Resolutions. CVPR 2018: 8042-8051 - [c68]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 - [c67]Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson:
Constant-Time Predictive Distributions for Gaussian Processes. ICML 2018: 4111-4120 - [c66]Jacob R. Gardner, Geoff Pleiss, Kilian Q. Weinberger, David Bindel, Andrew Gordon Wilson:
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. NeurIPS 2018: 7587-7597 - [c65]Johan Bjorck, Carla P. Gomes, Bart Selman, Kilian Q. Weinberger:
Understanding Batch Normalization. NeurIPS 2018: 7705-7716 - [e6]Sheila A. McIlraith, Kilian Q. Weinberger:
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18), New Orleans, Louisiana, USA, February 2-7, 2018. AAAI Press 2018 [contents] - [i34]Jacob R. Gardner, Geoff Pleiss, Ruihan Wu, Kilian Q. Weinberger, Andrew Gordon Wilson:
Product Kernel Interpolation for Scalable Gaussian Processes. CoRR abs/1802.08903 (2018) - [i33]Geoff Pleiss, Jacob R. Gardner, Kilian Q. Weinberger, Andrew Gordon Wilson:
Constant-Time Predictive Distributions for Gaussian Processes. CoRR abs/1803.06058 (2018) - [i32]Yan Wang, Lequn Wang, Yurong You, Xu Zou, Vincent Chen, Serena Li, Gao Huang, Bharath Hariharan, Kilian Q. Weinberger:
Resource Aware Person Re-identification across Multiple Resolutions. CoRR abs/1805.08805 (2018) - [i31]Qiantong Xu, Gao Huang, Yang Yuan, Chuan Guo, Yu Sun, Felix Wu, Kilian Q. Weinberger:
An empirical study on evaluation metrics of generative adversarial networks. CoRR abs/1806.07755 (2018) - [i30]Chuan Guo, Jared S. Frank, Kilian Q. Weinberger:
Low Frequency Adversarial Perturbation. CoRR abs/1809.08758 (2018) - [i29]Jacob R. Gardner, Geoff Pleiss, David Bindel, Kilian Q. Weinberger, Andrew Gordon Wilson:
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. CoRR abs/1809.11165 (2018) - [i28]Brian H. Wang, Yan Wang, Kilian Q. Weinberger, Mark Campbell:
Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking. CoRR abs/1810.08565 (2018) - [i27]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 abs/1810.11408 (2018) - [i26]Yan Wang, Wei-Lun Chao, Divyansh Garg, Bharath Hariharan, Mark Campbell, Kilian Q. Weinberger:
Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving. CoRR abs/1812.07179 (2018) - 2017
- [c64]Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse:
Discovering and Exploiting Additive Structure for Bayesian Optimization. AISTATS 2017: 1311-1319 - [c63]Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CVPR 2017: 2261-2269 - [c62]Paul Upchurch, Jacob R. Gardner, Geoff Pleiss, Robert Pless, Noah Snavely, Kavita Bala, Kilian Q. Weinberger:
Deep Feature Interpolation for Image Content Changes. CVPR 2017: 6090-6099 - [c61]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, Get M for Free. ICLR (Poster) 2017 - [c60]Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger:
On Calibration of Modern Neural Networks. ICML 2017: 1321-1330 - [c59]Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger:
On Fairness and Calibration. NIPS 2017: 5680-5689 - [i25]Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, Kilian Q. Weinberger:
Multi-Scale Dense Convolutional Networks for Efficient Prediction. CoRR abs/1703.09844 (2017) - [i24]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, get M for free. CoRR abs/1704.00109 (2017) - [i23]Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger:
On Calibration of Modern Neural Networks. CoRR abs/1706.04599 (2017) - [i22]Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger:
Memory-Efficient Implementation of DenseNets. CoRR abs/1707.06990 (2017) - [i21]Geoff Pleiss, Manish Raghavan, Felix Wu, Jon M. Kleinberg, Kilian Q. Weinberger:
On Fairness and Calibration. CoRR abs/1709.02012 (2017) - [i20]Felix Wu, Ni Lao, John Blitzer, Guandao Yang, Kilian Q. Weinberger:
Fast Reading Comprehension with ConvNets. CoRR abs/1711.04352 (2017) - [i19]Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger:
CondenseNet: An Efficient DenseNet using Learned Group Convolutions. CoRR abs/1711.09224 (2017) - 2016
- [c58]Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger:
Private Causal Inference. AISTATS 2016: 1308-1317 - [c57]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. ECCV (4) 2016: 646-661 - [c56]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks in the Frequency Domain. KDD 2016: 1475-1484 - [c55]Gao Huang, Chuan Guo, Matt J. Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger:
Supervised Word Mover's Distance. NIPS 2016: 4862-4870 - [e5]Maria-Florina Balcan, Kilian Q. Weinberger:
Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016. JMLR Workshop and Conference Proceedings 48, JMLR.org 2016 [contents] - [i18]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. CoRR abs/1603.09382 (2016) - [i17]Xilun Chen, Ben Athiwaratkun, Yu Sun, Kilian Q. Weinberger, Claire Cardie:
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. CoRR abs/1606.01614 (2016) - [i16]Gao Huang, Zhuang Liu, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CoRR abs/1608.06993 (2016) - [i15]Paul Upchurch, Jacob R. Gardner, Kavita Bala, Robert Pless, Noah Snavely, Kilian Q. Weinberger:
Deep Feature Interpolation for Image Content Changes. CoRR abs/1611.05507 (2016) - 2015
- [j7]Minmin Chen, Kilian Q. Weinberger, Zhixiang Eddie Xu, Fei Sha:
Marginalizing stacked linear denoising autoencoders. J. Mach. Learn. Res. 16: 3849-3875 (2015) - [c54]Zheng Chen, Minmin Chen, Kilian Q. Weinberger, Weixiong Zhang:
Marginalized Denoising for Link Prediction and Multi-Label Learning. AAAI 2015: 1707-1713 - [c53]Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen:
A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. AAAI 2015: 3210-3216 - [c52]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger:
Filtered Search for Submodular Maximization with Controllable Approximation Bounds. AISTATS 2015 - [c51]Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger:
Differentially Private Bayesian Optimization. ICML 2015: 918-927 - [c50]Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, Kilian Q. Weinberger:
From Word Embeddings To Document Distances. ICML 2015: 957-966 - [c49]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Neural Networks with the Hashing Trick. ICML 2015: 2285-2294 - [c48]Gustavo Malkomes, Matt J. Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley:
Fast Distributed k-Center Clustering with Outliers on Massive Data. NIPS 2015: 1063-1071 - [c47]Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Bayesian Active Model Selection with an Application to Automated Audiometry. NIPS 2015: 2386-2394 - [c46]Jacob R. Gardner, Xinyu Song, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Psychophysical Detection Testing with Bayesian Active Learning. UAI 2015: 286-295 - [i14]Zhixiang Eddie Xu, Jacob R. Gardner, Stephen Tyree, Kilian Q. Weinberger:
Compressed Support Vector Machines. CoRR abs/1501.06478 (2015) - [i13]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Neural Networks with the Hashing Trick. CoRR abs/1504.04788 (2015) - [i12]Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks. CoRR abs/1506.04449 (2015) - [i11]Jacob R. Gardner, Matt J. Kusner, Yixuan Li, Paul Upchurch, Kilian Q. Weinberger, John E. Hopcroft:
Deep Manifold Traversal: Changing Labels with Convolutional Features. CoRR abs/1511.06421 (2015) - 2014
- [j6]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle:
Classifier cascades and trees for minimizing feature evaluation cost. J. Mach. Learn. Res. 15(1): 2113-2144 (2014) - [c45]Matt J. Kusner, Wenlin Chen, Quan Zhou, Zhixiang Eddie Xu, Kilian Q. Weinberger, Yixin Chen:
Feature-Cost Sensitive Learning with Submodular Trees of Classifiers. AAAI 2014: 1939-1945 - [c44]Matt J. Kusner, Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal:
Stochastic Neighbor Compression. ICML 2014: 622-630 - [c43]Jacob R. Gardner, Matt J. Kusner, Zhixiang Eddie Xu, Kilian Q. Weinberger, John P. Cunningham:
Bayesian Optimization with Inequality Constraints. ICML 2014: 937-945 - [c42]Minmin Chen, Kilian Q. Weinberger, Fei Sha, Yoshua Bengio:
Marginalized Denoising Auto-encoders for Nonlinear Representations. ICML 2014: 1476-1484 - [c41]Zhixiang Eddie Xu, Gao Huang, Kilian Q. Weinberger, Alice X. Zheng:
Gradient boosted feature selection. KDD 2014: 522-531 - [c40]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger:
Fast flux discriminant for large-scale sparse nonlinear classification. KDD 2014: 621-630 - [c39]Gao Huang, Shiji Song, Zhixiang Eddie Xu, Kilian Q. Weinberger:
Transductive Minimax Probability Machine. ECML/PKDD (1) 2014: 579-594 - [e4]Zoubin Ghahramani, Max Welling, Corinna Cortes, Neil D. Lawrence, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada. 2014 [contents] - [i10]Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger:
Marginalizing Corrupted Features. CoRR abs/1402.7001 (2014) - [i9]Stephen Tyree, Jacob R. Gardner, Kilian Q. Weinberger, Kunal Agrawal, John Tran:
Parallel Support Vector Machines in Practice. CoRR abs/1404.1066 (2014) - [i8]Quan Zhou, Wenlin Chen, Shiji Song, Jacob R. Gardner, Kilian Q. Weinberger, Yixin Chen:
A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing. CoRR abs/1409.1976 (2014) - [i7]Matt J. Kusner, Nicholas I. Kolkin, Stephen Tyree, Kilian Q. Weinberger:
Stochastic Covariance Compression. CoRR abs/1412.1740 (2014) - 2013
- [c38]Wenlin Chen, Yixin Chen, Kilian Q. Weinberger, Qiang Lu, Xiaoping Chen:
Goal-Oriented Euclidean Heuristics with Manifold Learning. AAAI 2013 - [c37]Qiang Lu, Wenlin Chen, Yixin Chen, Kilian Q. Weinberger, Xiaoping Chen:
Utilizing Landmarks in Euclidean Heuristics for Optimal Planning. AAAI (Late-Breaking Developments) 2013 - [c36]Fred W. Prior, Sarah Jost Fouke, Tammie L. Benzinger, Alicia Boyd, Michael Chicoine, Sharath R. Cholleti, Matthew Kelsey, Bart Keogh, Lauren Kim, Mikhail Milchenko, David G. Politte, Stephen Tyree, Kilian Q. Weinberger, Daniel S. Marcus:
Predicting a multi-parametric probability map of active tumor extent using random forests. EMBC 2013: 6478-6481 - [c35]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen:
Cost-Sensitive Tree of Classifiers. ICML (1) 2013: 133-141 - [c34]Wenlin Chen, Kilian Q. Weinberger, Yixin Chen:
Maximum Variance Correction with Application to A* Search. ICML (1) 2013: 302-310 - [c33]Laurens van der Maaten, Minmin Chen, Stephen Tyree, Kilian Q. Weinberger:
Learning with Marginalized Corrupted Features. ICML (1) 2013: 410-418 - [c32]Zhixiang Eddie Xu, Matt J. Kusner, Gao Huang, Kilian Q. Weinberger:
Anytime Representation Learning. ICML (3) 2013: 1076-1084 - [c31]Minmin Chen, Alice X. Zheng, Kilian Q. Weinberger:
Fast Image Tagging. ICML (3) 2013: 1274-1282 - [e3]Christopher J. C. Burges, Léon Bottou, Zoubin Ghahramani, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. 2013 [contents] - [i6]Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha:
An alternative text representation to TF-IDF and Bag-of-Words. CoRR abs/1301.6770 (2013) - 2012
- [c30]Zhixiang Eddie Xu, Minmin Chen, Kilian Q. Weinberger, Fei Sha:
From sBoW to dCoT marginalized encoders for text representation. CIKM 2012: 1879-1884 - [c29]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha:
Marginalized Denoising Autoencoders for Domain Adaptation. ICML 2012 - [c28]Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle:
The Greedy Miser: Learning under Test-time Budgets. ICML 2012 - [c27]Laurens van der Maaten, Kilian Q. Weinberger:
Stochastic triplet embedding. MLSP 2012: 1-6 - [c26]Dor Kedem, Stephen Tyree, Kilian Q. Weinberger, Fei Sha, Gert R. G. Lanckriet:
Non-linear Metric Learning. NIPS 2012: 2582-2590 - [c25]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle, Dor Kedem:
Classifier Cascade for Minimizing Feature Evaluation Cost. AISTATS 2012: 218-226 - [e2]Peter L. Bartlett, Fernando C. N. Pereira, Christopher J. C. Burges, Léon Bottou, Kilian Q. Weinberger:
Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. 2012 [contents] - [i5]Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, Fei Sha:
Marginalized Denoising Autoencoders for Domain Adaptation. CoRR abs/1206.4683 (2012) - [i4]Zhixiang Eddie Xu, Kilian Q. Weinberger, Olivier Chapelle:
Distance Metric Learning for Kernel Machines. CoRR abs/1208.3422 (2012) - [i3]Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen:
Cost-Sensitive Tree of Classifiers. CoRR abs/1210.2771 (2012) - 2011
- [j5]Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng:
Boosted multi-task learning. Mach. Learn. 85(1-2): 149-173 (2011) - [c24]