
Sample Complexity of Kalman Filtering for Unknown Systems
In this paper, we consider the task of designing a Kalman Filter (KF) fo...
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SGPDT: Semantic Genetic Programming Based on Dynamic Targets
Semantic GP is a promising approach that introduces semantic awareness d...
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EdgeNets:Edge Varying Graph Neural Networks
Driven by the outstanding performance of neural networks in the structur...
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Finite Sample Analysis of Stochastic System Identification
In this paper, we analyze the finite sample complexity of stochastic sys...
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Monocular 3D Pose Recovery via Nonconvex Sparsity with Theoretical Analysis
For recovering 3D object poses from 2D images, a prevalent method is to ...
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Optimal Algorithms for Submodular Maximization with Distributed Constraints
We consider a class of discrete optimization problems that aim to maximi...
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Continual Learning for Sentence Representations Using Conceptors
Distributed representations of sentences have become ubiquitous in natur...
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Minibatch Processing in Spiking Neural Networks
Spiking neural networks (SNNs) are a promising candidate for biologicall...
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Optimal Structured Principal Subspace Estimation: Metric Entropy and Minimax Rates
Driven by a wide range of applications, many principal subspace estimati...
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EventGAN: Leveraging Large Scale Image Datasets for Event Cameras
Event cameras provide a number of benefits over traditional cameras, suc...
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Safe Predictors for Enforcing InputOutput Specifications
We present an approach for designing correctbyconstruction neural netw...
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CrossDomain 3D Equivariant Image Embeddings
Spherical convolutional networks have been introduced recently as tools ...
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Equivariant MultiView Networks
Several approaches to 3D vision tasks process multiple views of the inpu...
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An Exploration of Embodied Visual Exploration
Embodied computer vision considers perception for robots in general, uns...
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On the Capabilities and Limitations of Reasoning for Natural Language Understanding
Recent systems for natural language understanding are strong at overcomi...
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Encoding HighLevel Visual Attributes in Capsules for Explainable Medical Diagnoses
Deep neural networks are often called blackboxes due to their difficult...
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Learning Predictive Models From Observation and Interaction
Learning predictive models from interaction with the world allows an age...
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Depth Completion via Deep Basis Fitting
In this paper we consider the task of imageguided depth completion wher...
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Active Learning in Video Tracking
Active learning methods, like uncertainty sampling, combined with probab...
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Predicting with Proxies
Predictive analytics is increasingly used to guide decisionmaking in ma...
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Semantic variation operators for multidimensional genetic programming
Multidimensional genetic programming represents candidate solutions as s...
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CrossLingual Ability of Multilingual BERT: An Empirical Study
Recent work has exhibited the surprising crosslingual abilities of mult...
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A Baseline for FewShot Image Classification
Finetuning a deep network trained with the standard crossentropy loss ...
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All Graphs Lead to Rome: Learning Geometric and CycleConsistent Representations with Graph Convolutional Networks
Image feature matching is a fundamental part of many geometric computer ...
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Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses
Empirical research in Natural Language Processing (NLP) has adopted a na...
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Distributed AttackRobust Submodular Maximization for MultiRobot Planning
We aim to guard swarmrobotics applications against denialofservice (D...
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Labeling Panoramas with Spherical Hourglass Networks
With the recent proliferation of consumergrade 360 cameras, it is worth...
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Robustness Meets Deep Learning: An EndtoEnd Hybrid Pipeline for Unsupervised Learning of Egomotion
In this work, we propose a method that combines unsupervised deep learni...
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Black Box Submodular Maximization: Discrete and Continuous Settings
In this paper, we consider the problem of black box continuous submodula...
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Hierarchical TaxonomyAware and Attentional Graph Capsule RCNNs for LargeScale MultiLabel Text Classification
CNNs, RNNs, GCNs, and CapsNets have shown significant insights in repres...
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Equal Opportunity in Online Classification with Partial Feedback
We study an online classification problem with partial feedback in which...
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Question Answering as Global Reasoning over Semantic Abstractions
We propose a novel method for exploiting the semantic structure of text ...
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Joint Reasoning for Temporal and Causal Relations
Understanding temporal and causal relations between events is a fundamen...
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Stochastic optimization approaches to learning concise representations
We propose and study a method for learning interpretable features via st...
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EBIC: an open source software for highdimensional and big data biclustering analyses
Motivation: In this paper we present the latest release of EBIC, a next...
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PatientSpecific Effects of Medication Using Latent Force Models with Gaussian Processes
Multioutput Gaussian processes (GPs) are a flexible Bayesian nonparamet...
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Declarative LearningBased Programming as an Interface to AI Systems
Datadriven approaches are becoming more common as problemsolving techn...
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Neural Embedding for Physical Manipulations
In common realworld robotic operations, action and state spaces can be ...
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Estimating heterogeneous treatment effects with rightcensored data via causal survival forests
There is fastgrowing literature on estimating heterogeneous treatment e...
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Counting Roots of Polynomials over Z/p^2Z
Until recently, the only known method of finding the roots of polynomial...
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Bayesian Qlearning with Assumed Density Filtering
While offpolicy temporal difference methods have been broadly used in r...
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εLexicase selection: a probabilistic and multiobjective analysis of lexicase selection in continuous domains
Lexicase selection is a parent selection method that considers training ...
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ReliefBased Feature Selection: Introduction and Review
Feature selection plays a critical role in data mining, driven by increa...
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TreeStructured Boosting: Connections Between Gradient Boosted Stumps and Full Decision Trees
Additive models, such as produced by gradient boosting, and full interac...
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Stochastic Submodular Maximization: The Case of Coverage Functions
Stochastic optimization of continuous objectives is at the heart of mode...
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Ensemble representation learning: an analysis of fitness and survival for wrapperbased genetic programming methods
Recently we proposed a general, ensemblebased feature engineering wrapp...
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Toward the automated analysis of complex diseases in genomewide association studies using genetic programming
Machine learning has been gaining traction in recent years to meet the d...
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Decentralized Online Learning with Kernels
We consider multiagent stochastic optimization problems over reproducin...
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Using Task Descriptions in Lifelong Machine Learning for Improved Performance and ZeroShot Transfer
Knowledge transfer between tasks can improve the performance of learned ...
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Unsupervised learning of image motion by recomposing sequences
We propose a new method for learning a representation of image motion in...
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University of Pennsylvania
The University of Pennsylvania is a private Ivy League research university located in the University City neighborhood of Philadelphia, Pennsylvania.