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P3O: Policy-on Policy-off Policy Optimization
On-policy reinforcement learning (RL) algorithms have high sample comple...
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Continual Universal Object Detection
Object detection has improved significantly in recent years on multiple ...
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Fair Bayesian Optimization
Given the increasing importance of machine learning (ML) in our lives, a...
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Action recognition with spatial-temporal discriminative filter banks
Action recognition has seen a dramatic performance improvement in the la...
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SAVEHR: Self Attention Vector Representations for EHR based Personalized Chronic Disease Onset Prediction and Interpretability
Chronic disease progression is emerging as an important area of investme...
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OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations
We present a novel model called OCGAN for the classical problem of one-c...
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Region Proposal by Guided Anchoring
Region anchors are the cornerstone of modern object detection techniques...
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Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Neural Networks
We explore the problem of selectively forgetting a particular set of dat...
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MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals
Given multiple input signals, how can we infer node importance in a know...
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Scale-Aware Attention Network for Crowd Counting
In crowd counting datasets, people appear at different scales, depending...
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Incremental Learning for Metric-Based Meta-Learners
Majority of the modern meta-learning methods for few-shot classification...
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Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications
Trained on large datasets, deep learning (DL) can accurately classify vi...
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Scalable Logo Recognition using Proxies
Logo recognition is the task of identifying and classifying logos. Logo ...
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Language Models with Transformers
The Transformer architecture is superior to RNN-based models in computat...
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A Human-AI Loop Approach for Joint Keyword Discovery and Expectation Estimation in Micropost Event Detection
Microblogging platforms such as Twitter are increasingly being used in e...
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From Machine Reading Comprehension to Dialogue State Tracking: Bridging the Gap
Dialogue state tracking (DST) is at the heart of task-oriented dialogue ...
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Towards classification parity across cohorts
Recently, there has been a lot of interest in ensuring algorithmic fairn...
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Mixed-Privacy Forgetting in Deep Networks
We show that the influence of a subset of the training samples can be re...
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TextTubes for Detecting Curved Text in the Wild
We present a detector for curved text in natural images. We model scene ...
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MT-BioNER: Multi-task Learning for Biomedical Named Entity Recognition using Deep Bidirectional Transformers
Conversational agents such as Cortana, Alexa and Siri are continuously w...
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Interpretable Multi-Step Reasoning with Knowledge Extraction on Complex Healthcare Question Answering
Healthcare question answering assistance aims to provide customer health...
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Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation
Direct prediction of 3D body pose and shape remains a challenge even for...
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Differentially Private Consensus-Based Distributed Optimization
Data privacy is an important concern in learning, when datasets contain ...
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FACSIMILE: Fast and Accurate Scans From an Image in Less Than a Second
Current methods for body shape estimation either lack detail or require ...
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SelfORE: Self-supervised Relational Feature Learning for Open Relation Extraction
Open relation extraction is the task of extracting open-domain relation ...
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Unifying Homophily and Heterophily Network Transformation via Motifs
Higher-order proximity (HOP) is fundamental for most network embedding m...
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Recognizing Variables from their Data via Deep Embeddings of Distributions
A key obstacle in automated analytics and meta-learning is the inability...
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Can Adversarial Weight Perturbations Inject Neural Backdoors?
Adversarial machine learning has exposed several security hazards of neu...
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Imitation-Regularized Offline Learning
We study the problem of offline learning in automated decision systems u...
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Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources
With an increasing demand for training powers for deep learning algorith...
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A Linear Bandit for Seasonal Environments
Contextual bandit algorithms are extremely popular and widely used in re...
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Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access
Most prior work on task-oriented dialogue systems are restricted to a li...
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SelfNorm and CrossNorm for Out-of-Distribution Robustness
Normalization techniques are crucial in stabilizing and accelerating the...
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Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering
BERT model has been successfully applied to open-domain QA tasks. Howeve...
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Weakly Supervised Energy-Based Learning for Action Segmentation
This paper is about labeling video frames with action classes under weak...
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Large Scale Open-Set Deep Logo Detection
We present an open-set logo detection (OSLD) system, which can detect (l...
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Words aren't enough, their order matters: On the Robustness of Grounding Visual Referring Expressions
Visual referring expression recognition is a challenging task that requi...
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Coupled Recurrent Models for Polyphonic Music Composition
This work describes a novel recurrent model for music composition, which...
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Task2Vec: Task Embedding for Meta-Learning
We introduce a method to provide vectorial representations of visual cla...
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Communication-efficient distributed SGD with Sketching
Large-scale distributed training of neural networks is often limited by ...
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Policy-Driven Neural Response Generation for Knowledge-Grounded Dialogue Systems
Open-domain dialogue systems aim to generate relevant, informative and e...
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HyperStream: a Workflow Engine for Streaming Data
This paper describes HyperStream, a large-scale, flexible and robust sof...
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A Baseline for Few-Shot Image Classification
Fine-tuning a deep network trained with the standard cross-entropy loss ...
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Acoustic scene analysis with multi-head attention networks
Acoustic Scene Classification (ASC) is a challenging task, as a single s...
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Toward Understanding Catastrophic Forgetting in Continual Learning
We study the relationship between catastrophic forgetting and properties...
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GANMEX: One-vs-One Attributions using GAN-based Model Explainability
Attribution methods have been shown as promising approaches for identify...
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Competitive Multi-Agent Deep Reinforcement Learning with Counterfactual Thinking
Counterfactual thinking describes a psychological phenomenon that people...
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Robustness to Capitalization Errors in Named Entity Recognition
Robustness to capitalization errors is a highly desirable characteristic...
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The Unreasonable Effectiveness of Texture Transfer for Single Image Super-resolution
While implicit generative models such as GANs have shown impressive resu...
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Improving noise robustness of automatic speech recognition via parallel data and teacher-student learning
For real-world speech recognition applications, noise robustness is stil...
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