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01/05/2023
Beyond web-scraping: Crowd-sourcing a geographically diverse image dataset
Current dataset collection methods typically scrape large amounts of dat...
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01/28/2022
Bounding Training Data Reconstruction in Private (Deep) Learning
Differential privacy is widely accepted as the de facto method for preve...
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01/27/2022
A Systematic Study of Bias Amplification
Recent research suggests that predictions made by machine-learning model...
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01/20/2022
Omnivore: A Single Model for Many Visual Modalities
Prior work has studied different visual modalities in isolation and deve...
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01/20/2022
Revisiting Weakly Supervised Pre-Training of Visual Perception Models
Model pre-training is a cornerstone of modern visual recognition systems...
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01/04/2022
Submix: Practical Private Prediction for Large-Scale Language Models
Recent data-extraction attacks have exposed that language models can mem...
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12/23/2021
EIFFeL: Ensuring Integrity for Federated Learning
Federated learning (FL) enables clients to collaborate with a server to ...
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09/02/2021
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Secure multi-party computation (MPC) allows parties to perform computati...
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03/22/2021
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
Machine-learning systems such as self-driving cars or virtual assistants...
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02/23/2021
Measuring Data Leakage in Machine-Learning Models with Fisher Information
Machine-learning models contain information about the data they were tra...
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02/20/2021
Physical Reasoning Using Dynamics-Aware Models
A common approach to solving physical-reasoning tasks is to train a valu...
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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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12/11/2020
Data Appraisal Without Data Sharing
One of the most effective approaches to improving the performance of a m...
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07/09/2020
The Trade-Offs of Private Prediction
Machine learning models leak information about their training data every...
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06/18/2020
Forward Prediction for Physical Reasoning
Physical reasoning requires forward prediction: the ability to forecast ...
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01/09/2020
Secure multiparty computations in floating-point arithmetic
Secure multiparty computations enable the distribution of so-called shar...
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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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12/21/2019
Measuring Dataset Granularity
Despite the increasing visibility of fine-grained recognition in our fie...
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12/04/2019
Self-Supervised Learning of Pretext-Invariant Representations
The goal of self-supervised learning from images is to construct image r...
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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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11/08/2019
Certified Data Removal from Machine Learning Models
Good data stewardship requires removal of data at the request of the dat...
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10/11/2019
Privacy-Preserving Contextual Bandits
Contextual bandits are online learners that, given an input, select an a...
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08/15/2019
PHYRE: A New Benchmark for Physical Reasoning
Understanding and reasoning about physics is an important ability of int...
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06/06/2019
Does Object Recognition Work for Everyone?
The paper analyzes the accuracy of publicly available object-recognition...
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03/05/2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search
A plethora of recent work has shown that convolutional networks are not ...
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01/19/2019
Binary Image Selection (BISON): Interpretable Evaluation of Visual Grounding
Providing systems the ability to relate linguistic and visual content is...
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12/09/2018
Feature Denoising for Improving Adversarial Robustness
Adversarial attacks to image classification systems present challenges t...
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10/26/2018
Anytime Stereo Image Depth Estimation on Mobile Devices
Many real-world applications of stereo depth estimation in robotics requ...
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05/02/2018
Exploring the Limits of Weakly Supervised Pretraining
State-of-the-art visual perception models for a wide range of tasks rely...
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12/04/2017
Learning by Asking Questions
We introduce an interactive learning framework for the development and t...
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11/28/2017
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
Convolutional networks are the de-facto standard for analyzing spatio-te...
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11/27/2017
Separating Self-Expression and Visual Content in Hashtag Supervision
The variety, abundance, and structured nature of hashtags make them an i...
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11/25/2017
CondenseNet: An Efficient DenseNet using Learned Group Convolutions
Deep neural networks are increasingly used on mobile devices, where comp...
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10/31/2017
Countering Adversarial Images using Input Transformations
This paper investigates strategies that defend against adversarial-examp...
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07/21/2017
Memory-Efficient Implementation of DenseNets
The DenseNet architecture is highly computationally efficient as a resul...
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06/05/2017
Submanifold Sparse Convolutional Networks
Convolutional network are the de-facto standard for analysing spatio-tem...
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05/10/2017
Inferring and Executing Programs for Visual Reasoning
Existing methods for visual reasoning attempt to directly map inputs to ...
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12/29/2016
Learning Visual N-Grams from Web Data
Real-world image recognition systems need to recognize tens of thousands...
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12/20/2016
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
When building artificial intelligence systems that can reason and answer...
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08/25/2016
Densely Connected Convolutional Networks
Recent work has shown that convolutional networks can be substantially d...
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06/27/2016
Revisiting Visual Question Answering Baselines
Visual question answering (VQA) is an interesting learning setting for e...
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03/15/2016
Modeling Time Series Similarity with Siamese Recurrent Networks
Traditional techniques for measuring similarities between time series ar...
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12/05/2015
Approximated and User Steerable tSNE for Progressive Visual Analytics
Progressive Visual Analytics aims at improving the interactivity in exis...
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06/16/2015
Time Series Classification using the Hidden-Unit Logistic Model
We present a new model for time series classification, called the hidden...
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01/15/2013
