
DAP: DetectionAware Pretraining with Weak Supervision
This paper presents a detectionaware pretraining (DAP) approach, which...
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Learning Neural Generative Dynamics for Molecular Conformation Generation
We study how to generate molecule conformations (i.e., 3D structures) fr...
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Harnessing Distribution Ratio Estimators for Learning Agents with Quality and Diversity
QualityDiversity (QD) is a concept from Neuroevolution with some intrig...
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OffPolicy Interval Estimation with Lipschitz Value Iteration
Offpolicy evaluation provides an essential tool for evaluating the effe...
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Learning Guidance Rewards with Trajectoryspace Smoothing
Longterm temporal credit assignment is an important challenge in deep r...
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Efficient Competitive SelfPlay Policy Optimization
Reinforcement learning from selfplay has recently reported many success...
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Pretraining of Graph Neural Network for Modeling Effects of Mutations on ProteinProtein Binding Affinity
Modeling the effects of mutations on the binding affinity plays a crucia...
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Boosting Weakly Supervised Object Detection with Progressive Knowledge Transfer
In this paper, we propose an effective knowledge transfer framework to b...
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Accelerating Nonconvex Learning via Replica Exchange Langevin Diffusion
Langevin diffusion is a powerful method for nonconvex optimization, whic...
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Mutual Information Based Knowledge Transfer Under StateAction Dimension Mismatch
Deep reinforcement learning (RL) algorithms have achieved great success ...
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DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images
Change detection is a basic task of remote sensing image processing. The...
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Stein Variational Inference for Discrete Distributions
Gradientbased approximate inference methods, such as Stein variational ...
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Stateonly Imitation with Transition Dynamics Mismatch
Imitation Learning (IL) is a popular paradigm for training agents to ach...
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Disentangling Controllable Object through Video Prediction Improves Visual Reinforcement Learning
In many visionbased reinforcement learning (RL) problems, the agent con...
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Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification
Remote sensing image scene classification is a fundamental but challengi...
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DeepMask: an algorithm for cloud and cloud shadow detection in optical satellite remote sensing images using deep residual network
Detecting and masking cloud and cloud shadow from satellite remote sensi...
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HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding
Heterogeneous information network (HIN) embedding has gained increasing ...
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√(n)Regret for Learning in Markov Decision Processes with Function Approximation and Low Bellman Rank
In this paper, we consider the problem of online learning of Markov deci...
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Characterizing Attacks on Deep Reinforcement Learning
Deep reinforcement learning (DRL) has achieved great success in various ...
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Learning Belief Representations for Imitation Learning in POMDPs
We consider the problem of imitation learning from expert demonstrations...
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Exploration via Hindsight Goal Generation
Goaloriented reinforcement learning has recently been a practical frame...
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A gradual, semidiscrete approach to generative network training via explicit wasserstein minimization
This paper provides a simple procedure to fit generative networks to tar...
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Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
Recent advances in deep reinforcement learning algorithms have shown gre...
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Thresholding Bandit with Optimal Aggregate Regret
We consider the thresholding bandit problem, whose goal is to find arms ...
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Stochastic Variance Reduction for Deep Qlearning
Recent advances in deep reinforcement learning have achieved humanlevel...
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Knowledge Flow: Improve Upon Your Teachers
A zoo of deep nets is available these days for almost any given task, an...
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Overcoming Catastrophic Forgetting by Soft Parameter Pruning
Catastrophic forgetting is a challenge issue in continual learning when ...
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Anchor Box Optimization for Object Detection
In this paper, we propose a general approach to optimize anchor boxes fo...
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Understanding the Importance of Single Directions via Representative Substitution
Understanding the internal representations of deep neural networks (DNNs...
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emrQA: A Large Corpus for Question Answering on Electronic Medical Records
We propose a novel methodology to generate domainspecific largescale q...
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OffPolicy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy
When learning from a batch of logged bandit feedback, the discrepancy be...
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LargeMargin Classification in Hyperbolic Space
Representing data in hyperbolic space can effectively capture latent hie...
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Learning SelfImitating Diverse Policies
Deep reinforcement learning algorithms, including policy gradient method...
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Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling
Many efforts have been made to facilitate natural language processing ta...
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Learning to Explore with MetaPolicy Gradient
The performance of offpolicy learning, including deep Qlearning and de...
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LowNorm Graph Embedding
Learning distributed representations for nodes in graphs has become an i...
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Genetic Policy Optimization
Genetic algorithms have been widely used in many practical optimization ...
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Sampleefficient Policy Optimization with Stein Control Variate
Policy gradient methods have achieved remarkable successes in solving ch...
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Efficient Localized Inference for Large Graphical Models
We propose a new localized inference algorithm for answering marginaliza...
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Stochastic Variance Reduction for Policy Gradient Estimation
Recent advances in policy gradient methods and deep learning have demons...
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Empower Sequence Labeling with TaskAware Neural Language Model
Linguistic sequence labeling is a general modeling approach that encompa...
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On the Selective and Invariant Representation of DCNN for HighResolution Remote Sensing Image Recognition
Human vision possesses strong invariance in image recognition. The cogni...
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What do We Learn by Semantic Scene Understanding for Remote Sensing imagery in CNN framework?
Recently, deep convolutional neural network (DCNN) achieved increasingly...
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Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening
We propose a novel training algorithm for reinforcement learning which c...
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DPPred: An Effective Prediction Framework with Concise Discriminative Patterns
In the literature, two series of models have been proposed to address pr...
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Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks
Complex biological systems have been successfully modeled by biochemical...
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Exact Hybrid Covariance Thresholding for Joint Graphical Lasso
This paper considers the problem of estimating multiple related Gaussian...
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Tightening Fractional Covering Upper Bounds on the Partition Function for HighOrder Region Graphs
In this paper we present a new approach for tightening upper bounds on t...
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Jian Peng
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Assistant Professor in the Department of Computer Science at the University of Illinois at UrbanaChampaign