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An Adversarial Imitation Click Model for Information Retrieval
Modern information retrieval systems, including web search, ads placemen...
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MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Searching for novel molecules with desired chemical properties is crucia...
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Improving Knowledge Tracing via Pre-training Question Embeddings
Knowledge tracing (KT) defines the task of predicting whether students c...
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Sobolev Wasserstein GAN
Wasserstein GANs (WGANs), built upon the Kantorovich-Rubinstein (KR) dua...
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U-rank: Utility-oriented Learning to Rank with Implicit Feedback
Learning to rank with implicit feedback is one of the most important tas...
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Efficient Projection-Free Algorithms for Saddle Point Problems
The Frank-Wolfe algorithm is a classic method for constrained optimizati...
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Model-based Policy Optimization with Unsupervised Model Adaptation
Model-based reinforcement learning methods learn a dynamics model with r...
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AI Chiller: An Open IoT Cloud Based Machine Learning Framework for the Energy Saving of Building HVAC System via Big Data Analytics on the Fusion of BMS and Environmental Data
Energy saving and carbon emission reduction in buildings is one of the k...
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GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning
The heavy traffic congestion problem has always been a concern for moder...
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GIKT: A Graph-based Interaction Model for Knowledge Tracing
With the rapid development in online education, knowledge tracing (KT) h...
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Glancing Transformer for Non-Autoregressive Neural Machine Translation
Non-autoregressive neural machine translation achieves remarkable infere...
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Bidirectional Model-based Policy Optimization
Model-based reinforcement learning approaches leverage a forward dynamic...
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Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning
Interactive recommender system (IRS) has drawn huge attention because of...
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Active Sentence Learning by Adversarial Uncertainty Sampling in Discrete Space
In this paper, we focus on reducing the labeled data size for sentence l...
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Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip
Although Shannon theory states that it is asymptotically optimal to sepa...
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AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction
Learning effective feature interactions is crucial for click-through rat...
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Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency
Recent advances in large-scale optimal transport have greatly extended i...
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Multi-Agent Interactions Modeling with Correlated Policies
In multi-agent systems, complex interacting behaviors arise due to the h...
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Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Domain adaptation aims to leverage the supervision signal of source doma...
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Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling
Sequential recommendation task aims to predict user preference over item...
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Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching
Improving the efficiency of dispatching orders to vehicles is a research...
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Signal Instructed Coordination in Team Competition
Most existing models of multi-agent reinforcement learning (MARL) adopt ...
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Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning
In many real-world problems, a team of agents need to collaborate to max...
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Towards Making the Most of BERT in Neural Machine Translation
GPT-2 and BERT demonstrate the effectiveness of using pre-trained langua...
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Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence
Knowledge base is one of the main forms to represent information in a st...
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Dynamically Fused Graph Network for Multi-hop Reasoning
Text-based question answering (TBQA) has been studied extensively in rec...
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CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
Traffic signal control is an emerging application scenario for reinforce...
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Deep Landscape Forecasting for Real-time Bidding Advertising
The emergence of real-time auction in online advertising has drawn huge ...
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Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
User response prediction, which models the user preference w.r.t. the pr...
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Towards Efficient and Unbiased Implementation of Lipschitz Continuity in GANs
Lipschitz continuity recently becomes popular in generative adversarial ...
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Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space
In this paper we propose a hybrid architecture of actor-critic algorithm...
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Lipschitz Generative Adversarial Nets
In this paper we study the convergence of generative adversarial network...
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Blockchain based Privacy-Preserving Software Updates with Proof-of-Delivery for Internet of Things
A large number of IoT devices are connected via the Internet. However, m...
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A Blockchain-based Self-tallying Voting Scheme in Decentralized IoT
The Internet of Things (IoT) is experiencing explosive growth and has ga...
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An Efficient Linkable Group Signature for Payer Tracing in Anonymous Cryptocurrencies
Cryptocurrencies, led by bitcoin launched in 2009, have obtained wide at...
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Guiding the One-to-one Mapping in CycleGAN via Optimal Transport
CycleGAN is capable of learning a one-to-one mapping between two data di...
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Large-scale Interactive Recommendation with Tree-structured Policy Gradient
Reinforcement learning (RL) has recently been introduced to interactive ...
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Layout Design for Intelligent Warehouse by Evolution with Fitness Approximation
With the rapid growth of the express industry, intelligent warehouses th...
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Content Protection in Named Data Networking: Challenges and Potential Solutions
Information-Centric Networks (ICN) are promising alternatives to current...
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LRCoin: Leakage-resilient Cryptocurrency Based on Bitcoin for Data Trading in IoT
Currently, the number of Internet of Thing (IoT) devices making up the I...
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AdaShift: Decorrelation and Convergence of Adaptive Learning Rate Methods
Adam is shown not being able to converge to the optimal solution in cert...
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HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting
Spatio-temporal (ST) data, which represent multiple time series data cor...
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TGE-PS: Text-driven Graph Embedding with Pairs Sampling
In graphs with rich text information, constructing expressive graph repr...
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Deep Recurrent Survival Analysis
Survival analysis is a hotspot in statistical research for modeling time...
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Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising
In online advertising, the Internet users may be exposed to a sequence o...
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Understanding the Effectiveness of Lipschitz Constraint in Training of GANs via Gradient Analysis
This paper aims to bring a new perspective for understanding GANs, by de...
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Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
User response prediction is a crucial component for personalized informa...
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Path-Level Network Transformation for Efficient Architecture Search
We introduce a new function-preserving transformation for efficient neur...
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Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition
We study the problem of named entity recognition (NER) from electronic m...
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CoT: Cooperative Training for Generative Modeling
We propose Cooperative Training (CoT) for training generative models tha...
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