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Results for: Chandan Reddy

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Transfer learning for class imbalance problems with inadequate data
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An Individualized Super-Gaussian Single Microphone Speech Enhancement for Hearing Aid Users With Smartphone as an Assistive Device
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ICA based single microphone Blind Speech Separation technique using non-linear estimation of speech
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Transfer learning for class imbalance problems with inadequate data
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Weakly supervised nonnegative matrix factorization for user-driven clustering
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Pre-Processing Censored Survival Data Using Inverse Covariance Matrix Based Calibration
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Machine Learning for Survival Analysis: A Survey
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Probabilistic Social Sequential Model for Tour Recommendation
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Prediction and imputation in irregularly sampled clinical time series data using hierarchical linear dynamical models
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A Probabilistic Geographical Aspect-Opinion Model for Geo-Tagged Microblogs
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Survival Analysis based Framework for Early Prediction of Student Dropouts
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RODS: Rarity based Outlier Detection in a Sparse Coding Framework
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Predicting Complications in Critical Care Using Heterogeneous Clinical Data
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CRISP: Consensus Regularized Selection based Prediction
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Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization
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Geographical Latent Variable Models for Microblog Retrieval
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Regularized Weighted Linear Regression for High-dimensional Censored Data
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A Multi-Task Learning Formulation for Survival Analysis
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Biclustering neighborhood-based collaborative filtering method for top-n recommender systems
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Predicting gene functions from multiple biological sources using novel ensemble methods
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Doubly supervised embedding based on class labels and intrinsic clusters for high-dimensional data visualization
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PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering
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A distributed ensemble approach for mining healthcare data under privacy constraints
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Feature Grouping Using Weighted l1 Norm for High-Dimensional Data
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A Bayesian Perspective on Early Stage Event Prediction in Longitudinal Data
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L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization
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Probabilistic Group Recommendation Model for Crowdfunding Domains
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Project Success Prediction in Crowdfunding Environments
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Constrained elastic net based knowledge transfer for healthcare information exchange
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Project Recommendation Using Heterogeneous Traits in Crowdfunding
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Regularized Parametric Regression for High-dimensional Survival Analysis
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Early-Stage Event Prediction for Longitudinal Data
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Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
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Modeling the conflicting demands of parallelism and Temporal/Spatial locality in affine scheduling
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Neural Abstractive Text Summarization with Sequence-to-Sequence Models
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Deep Reinforcement Learning For Sequence to Sequence Models
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Short-Text Topic Modeling via Non-negative Matrix Factorization Enriched with Local Word-Context Correlations
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A Sparse Topic Model for Extracting Aspect-Specific Summaries from Online Reviews
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DyLink2Vec: Effective Feature Representation for Link Prediction in Dynamic Networks
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Predicting interval time for reciprocal link creation using survival analysis
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Recurrent Spatio-Temporal Point Process for Check-in Time Prediction
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LATTE: Latent Type Modeling for Biomedical Entity Linking
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A Hierarchical Attention Retrieval Model for Healthcare Question Answering
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Active Learning Technique for Multimodal Brain Tumor Segmentation Using Limited Labeled Images
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Discovering Product Defects and Solutions from Online User Generated Contents
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LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization
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An Attentive Spatio-Temporal Neural Model for Successive Point of Interest Recommendation
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Adversarial Factorization Autoencoder for Look-alike Modeling
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Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts
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Multi-Label Clinical Time-Series Generation via Conditional GAN
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ANTHEM: Attentive Hyperbolic Entity Model for Product Search
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Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms
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Spatio-Temporal Event Detection from Multiple Data Sources
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Text-to-SQL Generation for Question Answering on Electronic Medical Records
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Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data
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Probabilistic Topic Modeling for Comparative Analysis of Document Collections
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StructCoder: Structure-Aware Transformer for Code Generation
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CodeAttack: Code-based Adversarial Attacks for Pre-Trained Programming Language Models
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Towards Scalable Hyperbolic Neural Networks using Taylor Series Approximations
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Pseudo-Poincaré: A Unification Framework for Euclidean and Hyperbolic Graph Neural Networks
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XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence
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Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search
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Text Enriched Sparse Hyperbolic Graph Convolutional Networks
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Self-supervised Short-text Modeling through Auxiliary Context Generation
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Multilingual Code Snippets Training for Program Translation
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Deep Reinforcement Learning for Sequence-to-Sequence Models
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Self-supervised Transformer for Multivariate Clinical Time-Series with Missing Values
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Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks
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Fair Representation Learning using Interpolation Enabled Disentanglement
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Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction
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Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare
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Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models
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Workshop on Data-Efficient Machine Learning (DeMaL)
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Corpus-level and Concept-based Explanations for Interpretable Document Classification
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Interpretable Graph Similarity Computation via Differentiable Optimal Alignment of Node Embeddings
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T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification
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A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection
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Deliberate Self-Attention Network with Uncertainty Estimation for Multi-Aspect Review Rating Prediction
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Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes
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Supervised Contrastive Learning for Interpretable Long Document Comparison
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A Novel Tensor-Based Temporal Multi-Task Survival Analysis Model
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NoiseScope: Detecting Deepfake Images in a Blind Setting
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Efficient Implicit Unsupervised Text Hashing using Adversarial Autoencoder
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Image Generation Via Minimizing Fréchet Distance in Discriminator Feature Space
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Probabilistic Topic Modeling for Comparative Analysis of Document Collections
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Unified Energy-Based Generative Network for Supervised Image Hashing
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WindowSHAP: An Efficient Framework for Explaining Time-series Classifiers based on Shapley Values
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SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models
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A Self-Supervised Learning-based Approach to Clustering Multivariate Time-Series Data with Missing Values (SLAC-Time): An Application to Traumatic Brain Injury Phenotyping
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Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis
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A self-supervised learning-based approach to clustering multivariate time-series data with missing values (SLAC-Time): An application to TBI phenotyping
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Execution-based Code Generation using Deep Reinforcement Learning
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Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting
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Transformer-based Planning for Symbolic Regression
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Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs
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Image Hashing by Minimizing Discrete Component-wise Wasserstein Distance
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International Workshop on Multimodal Learning - 2023 Theme: Multimodal Learning with Foundation Models
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Identifying TBI Physiological States by Clustering of Multivariate Clinical Time-Series
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Supervised Contrastive Learning for Interpretable Long-Form Document Matching
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Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs

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