cornell university

∙ Ithaca , United States ∙ 0 followers

Cornell University is an educational institution that offers undergraduate majors, graduate, undergraduate and advanced degrees, and continuing education and outreach programs. Cornell has seven undergraduate colleges; a graduate school; professional-degree schools in business management, medicine, law, and veterinary medicine; and affiliated faculty units. Cornell University was founded in 1865 and is based in Ithaca, New York.

Torch-Struct: Deep Structured Prediction Library

The literature on structured prediction for NLP describes a rich collect...
02/03/2020 ∙ by Alexander M. Rush, et al. ∙ 48 ∙ share

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

Recent studies have discovered the vulnerability of Deep Neural Networks...
04/16/2019 ∙ by Xiaosen Wang, et al. ∙ 38 ∙ share

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AutoML using Metadata Language Embeddings

As a human choosing a supervised learning algorithm, it is natural to be...
10/08/2019 ∙ by Iddo Drori, et al. ∙ 36 ∙ share

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Mixed Reinforcement Learning with Additive Stochastic Uncertainty

Reinforcement learning (RL) methods often rely on massive exploration da...
02/28/2020 ∙ by Yao Mu, et al. ∙ 30 ∙ share

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Convolutional Networks with Dense Connectivity

Recent work has shown that convolutional networks can be substantially d...
01/08/2020 ∙ by Gao Huang, et al. ∙ 24 ∙ share

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A Simple Baseline for Bayesian Uncertainty in Deep Learning

We propose SWA-Gaussian (SWAG), a simple, scalable, and general purpose ...
02/07/2019 ∙ by Wesley Maddox, et al. ∙ 20 ∙ share

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

Detecting objects such as cars and pedestrians in 3D plays an indispensa...
06/14/2019 ∙ by Yurong You, et al. ∙ 20 ∙ share

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When Does Self-supervision Improve Few-shot Learning?

We present a technique to improve the generalization of deep representat...
10/08/2019 ∙ by Jong-Chyi Su, et al. ∙ 19 ∙ share

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Blameworthiness in Multi-Agent Settings

We provide a formal definition of blameworthiness in settings where mult...
03/11/2019 ∙ by Meir Friedenberg, et al. ∙ 18 ∙ share

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CAB: Continuous Adaptive Blending Estimator for Policy Evaluation and Learning

The ability to perform offline A/B-testing and off-policy learning using...
11/06/2018 ∙ by Yi Su, et al. ∙ 16 ∙ share

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Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

3D object detection is an essential task in autonomous driving. Recent t...
12/18/2018 ∙ by Yan Wang, et al. ∙ 16 ∙ share

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Confidence Calibration for Convolutional Neural Networks Using Structured Dropout

In classification applications, we often want probabilistic predictions ...
06/23/2019 ∙ by Zhilu Zhang, et al. ∙ 16 ∙ share

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Random Fourier Features via Fast Surrogate Leverage Weighted Sampling

In this paper, we propose a fast surrogate leverage weighted sampling st...
11/20/2019 ∙ by Fanghui Liu, et al. ∙ 16 ∙ share

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Unsupervised Learning of Probabilistic Diffeomorphic Registration for Images and Surfaces

Classical deformable registration techniques achieve impressive results ...
03/08/2019 ∙ by Adrian V. Dalca, et al. ∙ 13 ∙ share

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Efficient Rollout Strategies for Bayesian Optimization

Bayesian optimization (BO) is a class of sample-efficient global optimiz...
02/24/2020 ∙ by Eric Hans Lee, et al. ∙ 13 ∙ share

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Unsupervised Data Imputation via Variational Inference of Deep Subspaces

A wide range of systems exhibit high dimensional incomplete data. Accura...
03/08/2019 ∙ by Adrian V. Dalca, et al. ∙ 11 ∙ share

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Robust Local Features for Improving the Generalization of Adversarial Training

Adversarial training has been demonstrated as one of the most effective ...
09/23/2019 ∙ by Chubiao Song, et al. ∙ 11 ∙ share

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Efficient Policy Learning from Surrogate-Loss Classification Reductions

Recent work on policy learning from observational data has highlighted t...
02/12/2020 ∙ by Andrew Bennett, et al. ∙ 11 ∙ share

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Contextual-Bandit Based Personalized Recommendation with Time-Varying User Interests

A contextual bandit problem is studied in a highly non-stationary enviro...
02/29/2020 ∙ by Xiao Xu, et al. ∙ 11 ∙ share

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Low-volatility Anomaly and the Adaptive Multi-Factor Model

The paper explains the low-volatility anomaly from a new perspective. We...
03/16/2020 ∙ by Robert A. Jarrow, et al. ∙ 11 ∙ share

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Low Frequency Adversarial Perturbation

Recently, machine learning security has received significant attention. ...
09/24/2018 ∙ by Chuan Guo, et al. ∙ 10 ∙ share

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Neural Naturalist: Generating Fine-Grained Image Comparisons

We introduce the new Birds-to-Words dataset of 41k sentences describing ...
09/09/2019 ∙ by Maxwell Forbes, et al. ∙ 10 ∙ share

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Retouchdown: Adding Touchdown to StreetLearn as a Shareable Resource for Language Grounding Tasks in Street View

The Touchdown dataset (Chen et al., 2019) provides instructions by human...
01/10/2020 ∙ by Harsh Mehta, et al. ∙ 9 ∙ share

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Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction

Identifying changes in model parameters is fundamental in machine learni...
10/28/2018 ∙ by William Herlands, et al. ∙ 8 ∙ share

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Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition

Recurrent Neural Networks (RNNs) and their variants, such as Long-Short ...
11/19/2018 ∙ by Yu Pan, et al. ∙ 8 ∙ share

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Disentangling Influence: Using Disentangled Representations to Audit Model Predictions

Motivated by the need to audit complex and black box models, there has b...
06/20/2019 ∙ by Charles T. Marx, et al. ∙ 8 ∙ share

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Fair Learning-to-Rank from Implicit Feedback

Addressing unfairness in rankings has become an increasingly important p...
11/19/2019 ∙ by Himank Yadav, et al. ∙ 8 ∙ share

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On the Distribution of Minima in Intrinsic-Metric Rotation Averaging

Rotation Averaging is a non-convex optimization problem that determines ...
03/18/2020 ∙ by Kyle Wilson, et al. ∙ 8 ∙ share

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GeoStyle: Discovering Fashion Trends and Events

Understanding fashion styles and trends is of great potential interest t...
08/29/2019 ∙ by Utkarsh Mall, et al. ∙ 7 ∙ share

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Boosting Supervision with Self-Supervision for Few-shot Learning

We present a technique to improve the transferability of deep representa...
06/17/2019 ∙ by Jong-Chyi Su, et al. ∙ 6 ∙ share

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Approximate Causal Abstraction

Scientific models describe natural phenomena at different levels of abst...
06/27/2019 ∙ by Sander Beckers, et al. ∙ 4 ∙ share

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Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation

We consider the problem of segmenting a biomedical image into anatomical...
03/07/2019 ∙ by Adrian V. Dalca, et al. ∙ 3 ∙ share

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Positional Normalization

A widely deployed method for reducing the training time of deep neural n...
07/09/2019 ∙ by Boyi Li, et al. ∙ 3 ∙ share

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Adversarially robust transfer learning

Transfer learning, in which a network is trained on one task and re-purp...
05/20/2019 ∙ by Ali Shafahi, et al. ∙ 2 ∙ share

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An Unsupervised Learning Model for Deformable Medical Image Registration

We present an efficient learning-based algorithm for deformable, pairwis...
02/07/2018 ∙ by Guha Balakrishnan, et al. ∙ 1 ∙ share

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A Debiased MDI Feature Importance Measure for Random Forests

Tree ensembles such as Random Forests have achieved impressive empirical...
06/26/2019 ∙ by Xiao Li, et al. ∙ 1 ∙ share

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A Conceptually Well-Founded Characterization of Iterated Admissibility Using an "All I Know" Operator

Brandenburger, Friedenberg, and Keisler provide an epistemic characteriz...
07/22/2019 ∙ by Joseph Y. Halpern, et al. ∙ 1 ∙ share

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Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation

Deep neural networks with alternating convolutional, max-pooling and dec...
11/23/2015 ∙ by Sina Honari, et al. ∙ 0 ∙ share

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Asymmetric Minwise Hashing

Minwise hashing (Minhash) is a widely popular indexing scheme in practic...
11/14/2014 ∙ by Anshumali Shrivastava, et al. ∙ 0 ∙ share

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Compressed Counting

Counting is among the most fundamental operations in computing. For exam...
02/17/2008 ∙ by Ping Li, et al. ∙ 0 ∙ share

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Bayesian Q-learning with Assumed Density Filtering

While off-policy temporal difference methods have been broadly used in r...
12/09/2017 ∙ by Heejin Jeong, et al. ∙ 0 ∙ share

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Estimating the error variance in a high-dimensional linear model

The lasso has been studied extensively as a tool for estimating the coef...
12/06/2017 ∙ by Guo Yu, et al. ∙ 0 ∙ share

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DOTA: A Large-scale Dataset for Object Detection in Aerial Images

Object detection is an important and challenging problem in computer vis...
11/28/2017 ∙ by Gui-Song Xia, et al. ∙ 0 ∙ share

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CondenseNet: An Efficient DenseNet using Learned Group Convolutions

Deep neural networks are increasingly used on mobile devices, where comp...
11/25/2017 ∙ by Gao Huang, et al. ∙ 0 ∙ share

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Spectrally-normalized margin bounds for neural networks

This paper presents a margin-based multiclass generalization bound for n...
06/26/2017 ∙ by Peter Bartlett, et al. ∙ 0 ∙ share

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Detecting Bias in Black-Box Models Using Transparent Model Distillation

Black-box risk scoring models permeate our lives, yet are typically prop...
10/17/2017 ∙ by Sarah Tan, et al. ∙ 0 ∙ share

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Interpretable Vector AutoRegressions with Exogenous Time Series

The Vector AutoRegressive (VAR) model is fundamental to the study of mul...
11/09/2017 ∙ by Ines Wilms, et al. ∙ 0 ∙ share

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Traffic Optimization For a Mixture of Self-interested and Compliant Agents

This paper focuses on two commonly used path assignment policies for age...
09/27/2017 ∙ by Guni Sharon, et al. ∙ 0 ∙ share

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Learning Compositional Visual Concepts with Mutual Consistency

Compositionality of semantic concepts in image synthesis and analysis is...
11/16/2017 ∙ by Yunye Gong, et al. ∙ 0 ∙ share

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The Local Dimension of Deep Manifold

Based on our observation that there exists a dramatic drop for the singu...
11/05/2017 ∙ by Mengxiao Zhang, et al. ∙ 0 ∙ share

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