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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...
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07/23/2023
On the Effectiveness of Offline RL for Dialogue Response Generation
A common training technique for language models is teacher forcing (TF)....
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07/19/2023
IncDSI: Incrementally Updatable Document Retrieval
Differentiable Search Index is a recently proposed paradigm for document...
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03/27/2023
Learning Iterative Neural Optimizers for Image Steganography
Image steganography is the process of concealing secret information in i...
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03/27/2023
Unsupervised Adaptation from Repeated Traversals for Autonomous Driving
For a self-driving car to operate reliably, its perceptual system must g...
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02/20/2023
Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
Unsupervised out-of-distribution detection (OOD) seeks to identify out-o...
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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...
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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...
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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 ...
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06/16/2022
Differentially Private Multi-Party Data Release for Linear Regression
Differentially Private (DP) data release is a promising technique to dis...
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05/15/2022
Long-term Control for Dialogue Generation: Methods and Evaluation
Current approaches for controlling dialogue response generation are prim...
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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...
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03/29/2022
Learning to Detect Mobile Objects from LiDAR Scans Without Labels
Current 3D object detectors for autonomous driving are almost entirely t...
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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...
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02/25/2022
Does Label Differential Privacy Prevent Label Inference Attacks?
Label differential privacy (LDP) is a popular framework for training pri...
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01/10/2022
Language-driven Semantic Segmentation
We present LSeg, a novel model for language-driven semantic image segmen...
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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...
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10/21/2021
Is High Variance Unavoidable in RL? A Case Study in Continuous Control
Reinforcement learning (RL) experiments have notoriously high variance, ...
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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...
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07/09/2021
Online Adaptation to Label Distribution Shift
Machine learning models often encounter distribution shifts when deploye...
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06/02/2021
Towards Deeper Deep Reinforcement Learning
In computer vision and natural language processing, innovations in model...
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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...
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02/26/2021
Low-Precision Reinforcement Learning
Low-precision training has become a popular approach to reduce computati...
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02/09/2021
Making Paper Reviewing Robust to Bid Manipulation Attacks
Most computer science conferences rely on paper bidding to assign review...
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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...
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07/24/2020
MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation
Semi-supervised domain adaptation (SSDA) aims to adapt models from a lab...
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07/06/2020
Wasserstein Distances for Stereo Disparity Estimation
Existing approaches to depth or disparity estimation output a distributi...
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06/10/2020
Revisiting Few-sample BERT Fine-tuning
We study the problem of few-sample fine-tuning of BERT contextual repres...
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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...
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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...
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02/25/2020
On Feature Normalization and Data Augmentation
Modern neural network training relies heavily on data augmentation for i...
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02/24/2020
TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks
The complexity of large-scale neural networks can lead to poor understan...
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02/03/2020
Revisiting Meta-Learning as Supervised Learning
Recent years have witnessed an abundance of new publications and approac...
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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...
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01/08/2020
Convolutional Networks with Dense Connectivity
Recent work has shown that convolutional networks can be substantially d...
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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...
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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...
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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...
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09/28/2019
Integrated Triaging for Fast Reading Comprehension
Although according to several benchmarks automatic machine reading compr...
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07/09/2019
Positional Normalization
A widely deployed method for reducing the training time of deep neural n...
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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...
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05/17/2019
Simple Black-box Adversarial Attacks
We propose an intriguingly simple method for the construction of adversa...
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04/21/2019
BERTScore: Evaluating Text Generation with BERT
We propose BERTScore, an automatic evaluation metric for text generation...
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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...
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03/19/2019
Exact Gaussian Processes on a Million Data Points
Gaussian processes (GPs) are flexible models with state-of-the-art perfo...
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02/28/2019
FastFusionNet: New State-of-the-Art for DAWNBench SQuAD
In this technical report, we introduce FastFusionNet, an efficient varia...
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02/19/2019
Simplifying Graph Convolutional Networks
Graph Convolutional Networks (GCNs) and their variants have experienced ...
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01/13/2019
Gradient Regularized Budgeted Boosting
As machine learning transitions increasingly towards real world applicat...
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01/13/2019
Gradient Boosted Feature Selection
A feature selection algorithm should ideally satisfy four conditions: re...
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10/26/2018