Kilian Q. Weinberger

Affiliations:
  • Department of Computer Science and Engineering, Washington University in St. Louis


According to our database1, Kilian Q. Weinberger authored at least 163 papers between 2004 and 2024.

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Bibliography

2024
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation.
CoRR, 2024

Zero-shot Object-Level OOD Detection with Context-Aware Inpainting.
CoRR, 2024

Denoising Vision Transformers.
CoRR, 2024

2023
Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps.
CoRR, 2023

Correction with Backtracking Reduces Hallucination in Summarization.
CoRR, 2023

Pre-Training LiDAR-Based 3D Object Detectors Through Colorization.
CoRR, 2023

Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Latent Diffusion for Language Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

On the Effectiveness of Offline RL for Dialogue Response Generation.
Proceedings of the International Conference on Machine Learning, 2023

Unsupervised Out-of-Distribution Detection with Diffusion Inpainting.
Proceedings of the International Conference on Machine Learning, 2023

IncDSI: Incrementally Updatable Document Retrieval.
Proceedings of the International Conference on Machine Learning, 2023

Learning Iterative Neural Optimizers for Image Steganography.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Wav2Seq: Pre-Training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages.
Proceedings of the IEEE International Conference on Acoustics, 2023

Does Label Differential Privacy Prevent Label Inference Attacks?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Convolutional Networks with Dense Connectivity.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Does unsupervised grammar induction need pixels?
CoRR, 2022

Differentially private multi-party data release for linear regression.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Unsupervised Adaptation from Repeated Traversals for Autonomous Driving.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Long-term Control for Dialogue Generation: Methods and Evaluation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection in Self-Driving Cars.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Language-driven Semantic Segmentation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Fixed Neural Network Steganography: Train the images, not the network.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Is High Variance Unavoidable in RL? A Case Study in Continuous Control.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Performance-Efficiency Trade-Offs in Unsupervised Pre-Training for Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2022

Learning to Detect Mobile Objects from LiDAR Scans Without Labels.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Machine learning discovery of new phases in programmable quantum simulator snapshots.
CoRR, 2021

Towards Deeper Deep Reinforcement Learning.
CoRR, 2021

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection.
CoRR, 2021

Low-Precision Reinforcement Learning.
CoRR, 2021

Online Adaptation to Label Distribution Shift.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Deeper Deep Reinforcement Learning with Spectral Normalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Making Paper Reviewing Robust to Bid Manipulation Attacks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision.
Proceedings of the 38th International Conference on Machine Learning, 2021

Revisiting Few-sample BERT Fine-tuning.
Proceedings of the 9th International Conference on Learning Representations, 2021

Deep Co-Training with Task Decomposition for Semi-Supervised Domain Adaptation.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

On Feature Normalization and Data Augmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Understanding Decoupled and Early Weight Decay.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Characterizing the Loss Landscape in Non-Negative Matrix Factorization.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data.
CoRR, 2020

MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation.
CoRR, 2020

TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks.
CoRR, 2020

Revisiting Meta-Learning as Supervised Learning.
CoRR, 2020

Identifying Mislabeled Data using the Area Under the Margin Ranking.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Wasserstein Distances for Stereo Disparity Estimation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

BERTScore: Evaluating Text Generation with BERT.
Proceedings of the 8th International Conference on Learning Representations, 2020

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving.
Proceedings of the 8th International Conference on Learning Representations, 2020

Train in Germany, Test in the USA: Making 3D Object Detectors Generalize.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images.
IEEE Robotics Autom. Lett., 2019

SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning.
CoRR, 2019

Integrated Triaging for Fast Reading Comprehension.
CoRR, 2019

FastFusionNet: New State-of-the-Art for DAWNBench SQuAD.
CoRR, 2019

Gradient Regularized Budgeted Boosting.
CoRR, 2019

Low Frequency Adversarial Perturbation.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Exact Gaussian Processes on a Million Data Points.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Positional Normalization.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A New Defense Against Adversarial Images: Turning a Weakness into a Strength.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Anytime Stereo Image Depth Estimation on Mobile Devices.
Proceedings of the International Conference on Robotics and Automation, 2019

Simplifying Graph Convolutional Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Simple Black-box Adversarial Attacks.
Proceedings of the 36th International Conference on Machine Learning, 2019

Pseudo-LiDAR From Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Vision-only 3D Tracking for Self-Driving Cars.
Proceedings of the 15th IEEE International Conference on Automation Science and Engineering, 2019

2018
Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification.
Trans. Assoc. Comput. Linguistics, 2018

Deep Person Re-identification for Probabilistic Data Association in Multiple Pedestrian Tracking.
CoRR, 2018

An empirical study on evaluation metrics of generative adversarial networks.
CoRR, 2018

A Recap of the AAAI and IAAI 2018 Conferences and the EAAI Symposium.
AI Mag., 2018

GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Understanding Batch Normalization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Constant-Time Predictive Distributions for Gaussian Processes.
Proceedings of the 35th International Conference on Machine Learning, 2018

Multi-Scale Dense Networks for Resource Efficient Image Classification.
Proceedings of the 6th International Conference on Learning Representations, 2018

Resource Aware Person Re-Identification Across Multiple Resolutions.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

CondenseNet: An Efficient DenseNet Using Learned Group Convolutions.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Product Kernel Interpolation for Scalable Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Fast Reading Comprehension with ConvNets.
CoRR, 2017

Memory-Efficient Implementation of DenseNets.
CoRR, 2017

Multi-Scale Dense Convolutional Networks for Efficient Prediction.
CoRR, 2017

On Fairness and Calibration.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On Calibration of Modern Neural Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Snapshot Ensembles: Train 1, Get M for Free.
Proceedings of the 5th International Conference on Learning Representations, 2017

Deep Feature Interpolation for Image Content Changes.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Densely Connected Convolutional Networks.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Discovering and Exploiting Additive Structure for Bayesian Optimization.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Deep Feature Interpolation for Image Content Changes.
CoRR, 2016

Densely Connected Convolutional Networks.
CoRR, 2016

Supervised Word Mover's Distance.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Compressing Convolutional Neural Networks in the Frequency Domain.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Deep Networks with Stochastic Depth.
Proceedings of the Computer Vision - ECCV 2016, 2016

Private Causal Inference.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Marginalizing stacked linear denoising autoencoders.
J. Mach. Learn. Res., 2015

Compressed Support Vector Machines.
CoRR, 2015

Deep Manifold Traversal: Changing Labels with Convolutional Features.
CoRR, 2015

Compressing Convolutional Neural Networks.
CoRR, 2015

Psychophysical Detection Testing with Bayesian Active Learning.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Fast Distributed k-Center Clustering with Outliers on Massive Data.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Bayesian Active Model Selection with an Application to Automated Audiometry.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

From Word Embeddings To Document Distances.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Differentially Private Bayesian Optimization.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Compressing Neural Networks with the Hashing Trick.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Filtered Search for Submodular Maximization with Controllable Approximation Bounds.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

A Reduction of the Elastic Net to Support Vector Machines with an Application to GPU Computing.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Marginalized Denoising for Link Prediction and Multi-Label Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Classifier cascades and trees for minimizing feature evaluation cost.
J. Mach. Learn. Res., 2014

Parallel Support Vector Machines in Practice.
CoRR, 2014

Marginalizing Corrupted Features.
CoRR, 2014

Stochastic Covariance Compression.
CoRR, 2014

Transductive Minimax Probability Machine.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Gradient boosted feature selection.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Fast flux discriminant for large-scale sparse nonlinear classification.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

Stochastic Neighbor Compression.
Proceedings of the 31th International Conference on Machine Learning, 2014

Bayesian Optimization with Inequality Constraints.
Proceedings of the 31th International Conference on Machine Learning, 2014

Marginalized Denoising Auto-encoders for Nonlinear Representations.
Proceedings of the 31th International Conference on Machine Learning, 2014

Feature-Cost Sensitive Learning with Submodular Trees of Classifiers.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
An alternative text representation to TF-IDF and Bag-of-Words
CoRR, 2013

Cost-Sensitive Tree of Classifiers.
Proceedings of the 30th International Conference on Machine Learning, 2013

Anytime Representation Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

Learning with Marginalized Corrupted Features.
Proceedings of the 30th International Conference on Machine Learning, 2013

Fast Image Tagging.
Proceedings of the 30th International Conference on Machine Learning, 2013

Maximum Variance Correction with Application to A* Search.
Proceedings of the 30th International Conference on Machine Learning, 2013

Predicting a multi-parametric probability map of active tumor extent using random forests.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Utilizing Landmarks in Euclidean Heuristics for Optimal Planning.
Proceedings of the Late-Breaking Developments in the Field of Artificial Intelligence, 2013

Goal-Oriented Euclidean Heuristics with Manifold Learning.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
Classifier Cascade for Minimizing Feature Evaluation Cost.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Distance Metric Learning for Kernel Machines
CoRR, 2012

Non-linear Metric Learning.
Proceedings of the 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

Stochastic triplet embedding.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

The Greedy Miser: Learning under Test-time Budgets.
Proceedings of the 29th International Conference on Machine Learning, 2012

Marginalized Denoising Autoencoders for Domain Adaptation.
Proceedings of the 29th International Conference on Machine Learning, 2012

From sBoW to dCoT marginalized encoders for text representation.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
Boosted multi-task learning.
Mach. Learn., 2011

Web-Search Ranking with Initialized Gradient Boosted Regression Trees.
Proceedings of the Yahoo! Learning to Rank Challenge, 2011

Rapid Feature Learning with Stacked Linear Denoisers
CoRR, 2011

Parallel boosted regression trees for web search ranking.
Proceedings of the 20th International Conference on World Wide Web, 2011

Co-Training for Domain Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Automatic Feature Decomposition for Single View Co-training.
Proceedings of the 28th International Conference on Machine Learning, 2011

Spam or ham?: characterizing and detecting fraudulent "not spam" reports in web mail systems.
Proceedings of the 8th Annual Collaboration, 2011

2010
Convex Optimizations for Distance Metric Learning and Pattern Classification [Applications Corner].
IEEE Signal Process. Mag., 2010

Learning to rank with (a lot of) word features.
Inf. Retr., 2010

Large Margin Multi-Task Metric Learning.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Decoding Ipsilateral Finger Movements from ECoG Signals in Humans.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Multi-task learning for boosting with application to web search ranking.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009
Distance Metric Learning for Large Margin Nearest Neighbor Classification.
J. Mach. Learn. Res., 2009

Unsupervised image ranking.
Proceedings of the First ACM workshop on Large-scale multimedia retrieval and mining, 2009

Feature hashing for large scale multitask learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Supervised semantic indexing.
Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

2008
Large Margin Taxonomy Embedding for Document Categorization.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Resolving tag ambiguity.
Proceedings of the 16th International Conference on Multimedia 2008, 2008

Learning a Metric for Music Similarity.
Proceedings of the ISMIR 2008, 2008

Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Fast solvers and efficient implementations for distance metric learning.
Proceedings of the Machine Learning, 2008

2007
Metric Learning for Kernel Regression.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

2006
Unsupervised Learning of Image Manifolds by Semidefinite Programming.
Int. J. Comput. Vis., 2006

Graph Laplacian Regularization for Large-Scale Semidefinite Programming.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

An Introduction to Nonlinear Dimensionality Reduction by Maximum Variance Unfolding.
Proceedings of the Proceedings, 2006

Spectral Methods for Dimensionality Reduction.
Proceedings of the Semi-Supervised Learning, 2006

2005
Distance Metric Learning for Large Margin Nearest Neighbor Classification.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Hierarchical Distributed Representations for Statistical Language Modeling.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Learning a kernel matrix for nonlinear dimensionality reduction.
Proceedings of the Machine Learning, 2004


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