Kilian Q. Weinberger

research

∙ 09/21/2023

Unsupervised Domain Adaptation for Self-Driving from Past Traversal Features

The rapid development of 3D object detection systems for self-driving ca...

0 Travis Zhang, et al. ∙

research

∙ 07/23/2023

On the Effectiveness of Offline RL for Dialogue Response Generation

A common training technique for language models is teacher forcing (TF)....

0 Paloma Sodhi, et al. ∙

research

∙ 07/19/2023

IncDSI: Incrementally Updatable Document Retrieval

Differentiable Search Index is a recently proposed paradigm for document...

0 Varsha Kishore, et al. ∙

research

∙ 03/27/2023

Learning Iterative Neural Optimizers for Image Steganography

Image steganography is the process of concealing secret information in i...

0 Xiangyu Chen, et al. ∙

research

∙ 03/27/2023

Unsupervised Adaptation from Repeated Traversals for Autonomous Driving

For a self-driving car to operate reliably, its perceptual system must g...

0 Yurong You, et al. ∙

research

∙ 02/20/2023

Unsupervised Out-of-Distribution Detection with Diffusion Inpainting

Unsupervised out-of-distribution detection (OOD) seeks to identify out-o...

0 Zhenzhen Liu, et al. ∙

research

∙ 10/19/2022

Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning

Gradient inversion attack enables recovery of training samples from mode...

0 Ruihan Wu, et al. ∙

research

∙ 09/23/2022

Image-to-Image Translation for Autonomous Driving from Coarsely-Aligned Image Pairs

A self-driving car must be able to reliably handle adverse weather condi...

0 Youya Xia, et al. ∙

research

∙ 08/01/2022

Ithaca365: Dataset and Driving Perception under Repeated and Challenging Weather Conditions

Advances in perception for self-driving cars have accelerated in recent ...

0 Carlos A. Diaz-Ruiz, et al. ∙

research

∙ 06/16/2022

Differentially Private Multi-Party Data Release for Linear Regression

Differentially Private (DP) data release is a promising technique to dis...

11 Ruihan Wu, et al. ∙

research

∙ 05/15/2022

Long-term Control for Dialogue Generation: Methods and Evaluation

Current approaches for controlling dialogue response generation are prim...

8 Ramya Ramakrishnan, et al. ∙

research

∙ 05/02/2022

Wav2Seq: Pre-training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages

We introduce Wav2Seq, the first self-supervised approach to pre-train bo...

0 Felix Wu, et al. ∙

research

∙ 03/29/2022

Learning to Detect Mobile Objects from LiDAR Scans Without Labels

Current 3D object detectors for autonomous driving are almost entirely t...

33 Yurong You, et al. ∙

research

∙ 03/22/2022

Hindsight is 20/20: Leveraging Past Traversals to Aid 3D Perception

Self-driving cars must detect vehicles, pedestrians, and other traffic p...

3 Yurong You, et al. ∙

research

∙ 02/25/2022

Does Label Differential Privacy Prevent Label Inference Attacks?

Label differential privacy (LDP) is a popular framework for training pri...

0 Ruihan Wu, et al. ∙

research

∙ 01/10/2022

Language-driven Semantic Segmentation

We present LSeg, a novel model for language-driven semantic image segmen...

7 Boyi Li, et al. ∙

research

∙ 12/20/2021

Machine learning discovery of new phases in programmable quantum simulator snapshots

Machine learning has recently emerged as a promising approach for studyi...

56 Cole Miles, et al. ∙

research

∙ 10/21/2021

Is High Variance Unavoidable in RL? A Case Study in Continuous Control

Reinforcement learning (RL) experiments have notoriously high variance, ...

4 Johan Bjorck, et al. ∙

research

∙ 09/14/2021

Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition

This paper is a study of performance-efficiency trade-offs in pre-traine...

0 Felix Wu, et al. ∙

research

∙ 07/09/2021

Online Adaptation to Label Distribution Shift

Machine learning models often encounter distribution shifts when deploye...

0 Ruihan Wu, et al. ∙

research

∙ 06/02/2021

Towards Deeper Deep Reinforcement Learning

In computer vision and natural language processing, innovations in model...

21 Johan Bjorck, et al. ∙

research

∙ 03/26/2021

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection

Self-driving cars must detect other vehicles and pedestrians in 3D to pl...

0 Yurong You, et al. ∙

research

∙ 02/26/2021

Low-Precision Reinforcement Learning

Low-precision training has become a popular approach to reduce computati...

51 Johan Bjorck, et al. ∙

research

∙ 02/09/2021

Making Paper Reviewing Robust to Bid Manipulation Attacks

Most computer science conferences rely on paper bidding to assign review...

0 Ruihan Wu, et al. ∙

research

∙ 11/06/2020

Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data

Machine learning models are a powerful theoretical tool for analyzing da...

0 Cole Miles, et al. ∙

research

∙ 07/24/2020

MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation

Semi-supervised domain adaptation (SSDA) aims to adapt models from a lab...

13 Luyu Yang, et al. ∙

research

∙ 07/06/2020

Wasserstein Distances for Stereo Disparity Estimation

Existing approaches to depth or disparity estimation output a distributi...

0 Divyansh Garg, et al. ∙

research

∙ 06/10/2020

Revisiting Few-sample BERT Fine-tuning

We study the problem of few-sample fine-tuning of BERT contextual repres...

0 Tianyi Zhang, et al. ∙

research

∙ 05/17/2020

Train in Germany, Test in The USA: Making 3D Object Detectors Generalize

In the domain of autonomous driving, deep learning has substantially imp...

18 Yan Wang, et al. ∙

research

∙ 04/07/2020

End-to-End Pseudo-LiDAR for Image-Based 3D Object Detection

Reliable and accurate 3D object detection is a necessity for safe autono...

6 Rui Qian, et al. ∙

research

∙ 02/25/2020

On Feature Normalization and Data Augmentation

Modern neural network training relies heavily on data augmentation for i...

19 Boyi Li, et al. ∙

research

∙ 02/24/2020

TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks

The complexity of large-scale neural networks can lead to poor understan...

0 Chuan Guo, et al. ∙

research

∙ 02/03/2020

Revisiting Meta-Learning as Supervised Learning

Recent years have witnessed an abundance of new publications and approac...

0 Wei-Lun Chao, et al. ∙

research

∙ 01/28/2020

Identifying Mislabeled Data using the Area Under the Margin Ranking

Not all data in a typical training set help with generalization; some sa...

26 Geoff Pleiss, et al. ∙

research

∙ 01/08/2020

Convolutional Networks with Dense Connectivity

Recent work has shown that convolutional networks can be substantially d...

24 Gao Huang, et al. ∙

research

∙ 11/12/2019

SimpleShot: Revisiting Nearest-Neighbor Classification for Few-Shot Learning

Few-shot learners aim to recognize new object classes based on a small n...

0 Yan Wang, et al. ∙

research

∙ 10/30/2019

LDLS: 3-D Object Segmentation Through Label Diffusion From 2-D Images

Object segmentation in three-dimensional (3-D) point clouds is a critica...

11 Brian H. Wang, et al. ∙

research

∙ 10/16/2019

A New Defense Against Adversarial Images: Turning a Weakness into a Strength

Natural images are virtually surrounded by low-density misclassified reg...

0 Tao Yu, et al. ∙

research

∙ 09/28/2019

Integrated Triaging for Fast Reading Comprehension

Although according to several benchmarks automatic machine reading compr...

0 Felix Wu, et al. ∙

research

∙ 07/09/2019

Positional Normalization

A widely deployed method for reducing the training time of deep neural n...

3 Boyi Li, et al. ∙

research

∙ 06/14/2019

Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Driving

Detecting objects such as cars and pedestrians in 3D plays an indispensa...

20 Yurong You, et al. ∙

research

∙ 05/17/2019

Simple Black-box Adversarial Attacks

We propose an intriguingly simple method for the construction of adversa...

7 Chuan Guo, et al. ∙

research

∙ 04/21/2019

BERTScore: Evaluating Text Generation with BERT

We propose BERTScore, an automatic evaluation metric for text generation...

0 Tianyi Zhang, et al. ∙

research

∙ 04/16/2019

AT-GAN: A Generative Attack Model for Adversarial Transferring on Generative Adversarial Nets

Recent studies have discovered the vulnerability of Deep Neural Networks...

38 Xiaosen Wang, et al. ∙

research

∙ 03/19/2019

Exact Gaussian Processes on a Million Data Points

Gaussian processes (GPs) are flexible models with state-of-the-art perfo...

32 Ke Alexander Wang, et al. ∙

research

∙ 02/28/2019

FastFusionNet: New State-of-the-Art for DAWNBench SQuAD

In this technical report, we introduce FastFusionNet, an efficient varia...

0 Felix Wu, et al. ∙

research

∙ 02/19/2019

Simplifying Graph Convolutional Networks

Graph Convolutional Networks (GCNs) and their variants have experienced ...

0 Felix Wu, et al. ∙

research

∙ 01/13/2019

Gradient Regularized Budgeted Boosting

As machine learning transitions increasingly towards real world applicat...

0 Zhixiang Eddie Xu, et al. ∙

research

∙ 01/13/2019

Gradient Boosted Feature Selection

A feature selection algorithm should ideally satisfy four conditions: re...

0 Zhixiang Eddie Xu, et al. ∙

research

∙ 10/26/2018

Anytime Stereo Image Depth Estimation on Mobile Devices

Many real-world applications of stereo depth estimation in robotics requ...

4 Yan Wang, et al. ∙

Kilian Q. Weinberger

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