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Distributed Bootstrap for Simultaneous Inference Under High Dimensionality
We propose a distributed bootstrap method for simultaneous inference on ...
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Self-supervised learning for fast and scalable time series hyper-parameter tuning
Hyper-parameters of time series models play an important role in time se...
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Derivative-Free Reinforcement Learning: A Review
Reinforcement learning is about learning agent models that make the best...
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NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application
Pre-trained language models (PLMs) like BERT have made great progress in...
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NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning
Offline reinforcement learning (RL) aims at learning a good policy from ...
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Scale-free Network-based Differential Evolution
Some recent research reveals that a topological structure in meta-heuris...
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Interactive Search Based on Deep Reinforcement Learning
With the continuous development of machine learning technology, major e-...
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Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning
Human judgments of word similarity have been a popular method of evaluat...
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An authenticated and secure accounting system for international emissions trading
Expanding multi-country emissions trading system is considered as crucia...
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OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs
Providing appropriate structures around human resources can streamline o...
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Angular Embedding: A New Angular Robust Principal Component Analysis
As a widely used method in machine learning, principal component analysi...
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RetroXpert: Decompose Retrosynthesis Prediction like a Chemist
Retrosynthesis is the process of recursively decomposing target molecule...
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Mining Generalized Features for Detecting AI-Manipulated Fake Faces
Recently, AI-manipulated face techniques have developed rapidly and cons...
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Error Bounds of Imitating Policies and Environments
Imitation learning trains a policy by mimicking expert demonstrations. V...
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Difference-in-Differences: Bridging Normalization and Disentanglement in PG-GAN
What mechanisms causes GAN's entanglement? Although developing disentang...
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TurboTransformers: An Efficient GPU Serving System For Transformer Models
The transformer is the most critical algorithm innovation of the Nature ...
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Reinforced Epidemic Control: Saving Both Lives and Economy
Saving lives or economy is a dilemma for epidemic control in most cities...
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QPLEX: Duplex Dueling Multi-Agent Q-Learning
We explore value-based multi-agent reinforcement learning (MARL) in the ...
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Local Neighbor Propagation Embedding
Manifold Learning occupies a vital role in the field of nonlinear dimens...
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Hercules: An Autonomous Logistic Vehicle for Contact-less Goods Transportation During the COVID-19 Outbreak
Since December 2019, the coronavirus disease 2019 (COVID-19) has spread ...
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Validation Set Evaluation can be Wrong: An Evaluator-Generator Approach for Maximizing Online Performance of Ranking in E-commerce
Learning-to-rank (LTR) has become a key technology in E-commerce applica...
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Beyond the Ground-Truth: An Evaluator-Generator Framework for Group-wise Learning-to-Rank in E-Commerce
Learning-to-rank (LTR) has become a key technology in E-commerce applica...
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Design of Convergence-Optimized Non-binary LDPC Codes over Binary Erasure Channel
In this letter, we present a hybrid iterative decoder for non-binary low...
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Novelty-Prepared Few-Shot Classification
Few-shot classification algorithms can alleviate the data scarceness iss...
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Simultaneous Inference for Massive Data: Distributed Bootstrap
In this paper, we propose a bootstrap method applied to massive data pro...
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Residual Bootstrap Exploration for Bandit Algorithms
In this paper, we propose a novel perturbation-based exploration method ...
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Temporal-adaptive Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (HRL) helps address large-scale and ...
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Robust Data-driven Profile-based Pricing Schemes
To enable an efficient electricity market, a good pricing scheme is of v...
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Optimal Electricity Storage Sharing Mechanism for Single Peaked Time-of-Use Pricing Scheme
Sharing economy has disrupted many industries. We foresee that electrici...
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A Data-driven Storage Control Framework for Dynamic Pricing
Dynamic pricing is both an opportunity and a challenge to the demand sid...
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Improving Fictitious Play Reinforcement Learning with Expanding Models
Fictitious play with reinforcement learning is a general and effective f...
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Vulnerability Analysis for Data Driven Pricing Schemes
Data analytics and machine learning techniques are being rapidly adopted...
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On Value Discrepancy of Imitation Learning
Imitation learning trains a policy from expert demonstrations. Imitation...
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Debugging Crashes using Continuous Contrast Set Mining
Facebook operates a family of services used by over two billion people d...
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Rule Designs for Optimal Online Game Matchmaking
Online games are the most popular form of entertainment among youngsters...
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Conductor Galloping Prediction on Imbalanced Datasets: SVM with Smart Sampling
Conductor galloping is the high-amplitude, low-frequency oscillation of ...
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Signal Combination for Language Identification
Google's multilingual speech recognition system combines low-level acous...
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Hierarchic Neighbors Embedding
Manifold learning now plays a very important role in machine learning an...
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LabelECG: A Web-based Tool for Distributed Electrocardiogram Annotation
Electrocardiography plays an essential role in diagnosing and screening ...
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On the Robustness of Median Sampling in Noisy Evolutionary Optimization
In real-world optimization tasks, the objective (i.e., fitness) function...
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Towards AutoML in the presence of Drift: first results
Research progress in AutoML has lead to state of the art solutions that ...
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Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
Reinforcement learning aims at searching the best policy model for decis...
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Key Ingredients of Self-Driving Cars
Over the past decade, many research articles have been published in the ...
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Knowledge-augmented Column Networks: Guiding Deep Learning with Advice
Recently, deep models have had considerable success in several tasks, es...
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Reinforcement Learning Experience Reuse with Policy Residual Representation
Experience reuse is key to sample-efficient reinforcement learning. One ...
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Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit
An automatic machine learning (AutoML) task is to select the best algori...
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Computer-aided Detection of Squamous Carcinoma of the Cervix in Whole Slide Images
Goal: Squamous cell carcinoma of cervix is one of the most prevalent can...
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Automatic Calibration of Multiple 3D LiDARs in Urban Environments
Multiple LiDARs have progressively emerged on autonomous vehicles for re...
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A Novel Dual-Lidar Calibration Algorithm Using Planar Surfaces
Multiple lidars are prevalently used on mobile vehicles for rendering a ...
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Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice
Recently, deep models have been successfully applied in several applicat...
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