
ZeroShot Knowledge Distillation from a DecisionBased BlackBox Model
Knowledge distillation (KD) is a successful approach for deep neural net...
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Acousticbased Object Detection for Pedestrian Using Smartphone
Walking while using a smartphone is becoming a major pedestrian safety c...
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DataFree Knowledge Distillation with Soft Targeted Transfer Set Synthesis
Knowledge distillation (KD) has proved to be an effective approach for d...
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Convolutional Neural Network Pruning with Structural Redundancy Reduction
Convolutional neural network (CNN) pruning has become one of the most su...
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Exploring Adversarial Robustness of Deep Metric Learning
Deep Metric Learning (DML), a widelyused technique, involves learning a...
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NonlineofSight Imaging via Neural Transient Fields
We present a neural modeling framework for NonLineofSight (NLOS) imag...
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Accelerated NMR Spectroscopy: Merge Optimization with Deep Learning
Multidimensional NMR spectroscopy is an invaluable biophysical tool in ...
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A Note on the Likelihood Ratio Test in HighDimensional Exploratory Factor Analysis
The likelihood ratio test is widely used in exploratory factor analysis ...
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Abstract Universal Approximation for Neural Networks
With growing concerns about the safety and robustness of neural networks...
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Learning compositional models of robot skills for task and motion planning
The objective of this work is to augment the basic abilities of a robot ...
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TOFU: TargetOriented FUzzer
Program fuzzing—providing randomly constructed inputs to a computer prog...
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TOFU:TargetOrienter FUzzer
Program fuzzingproviding randomly constructed inputs to a computer prog...
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Semantic Robustness of Models of Source Code
Deep neural networks are vulnerable to adversarial examples  small inpu...
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Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy
Since the concept of deep learning (DL) was formally proposed in 2006, i...
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Investigating Channel Pruning through Structural Redundancy Reduction  A Statistical Study
Most existing channel pruning methods formulate the pruning task from a ...
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Speeding up convolutional networks pruning with coarse ranking
Channelbased pruning has achieved significant successes in accelerating...
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Singleshot Channel Pruning Based on Alternating Direction Method of Multipliers
Channel pruning has been identified as an effective approach to construc...
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Regret bounds for meta Bayesian optimization with an unknown Gaussian process prior
Bayesian optimization usually assumes that a Bayesian prior is given. Ho...
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Learning sparse relational transition models
We present a representation for describing transition models in complex ...
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Learning to guide task and motion planning using scorespace representation
In this paper, we propose a learning algorithm that speeds up the search...
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Fastconverging Conditional Generative Adversarial Networks for Image Synthesis
Building on top of the success of generative adversarial networks (GANs)...
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Active model learning and diverse action sampling for task and motion planning
The objective of this work is to augment the basic abilities of a robot ...
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Deep Reinforcement Learning of Cell Movement in the Early Stage of C. elegans Embryogenesis
Cell movement in the early phase of C. elegans development is regulated ...
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Ensemble Bayesian Optimization
Bayesian Optimization (BO) has been shown to be a very effective paradig...
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Batched Highdimensional Bayesian Optimization via Structural Kernel Learning
Optimization of highdimensional blackbox functions is an extremely cha...
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Maxvalue Entropy Search for Efficient Bayesian Optimization
Entropy Search (ES) and Predictive Entropy Search (PES) are popular and ...
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Focused ModelLearning and Planning for NonGaussian Continuous StateAction Systems
We introduce a framework for model learning and planning in stochastic d...
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Optimization as Estimation with Gaussian Processes in Bandit Settings
Recently, there has been rising interest in Bayesian optimization  the...
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Sparse multiview matrix factorisation: a multivariate approach to multiple tissue comparisons
Gene expression levels in a population vary extensively across tissues. ...
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Zi Wang
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