
Sound Probabilistic Inference via Guide Types
Probabilistic programming languages aim to describe and automate Bayesia...
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ExpectedCost Analysis for Probabilistic Programs and SemanticsLevel Adaption of Optional Stopping Theorems
In this article, we present a semanticslevel adaption of the Optional S...
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3DMNDT:3D multiview registration method based on the normal distributions transform
The normal distributions transform (NDT) is an effective paradigm for th...
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Minimum Cost Flows, MDPs, and ℓ_1Regression in Nearly Linear Time for Dense Instances
In this paper we provide new randomized algorithms with improved runtime...
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HighDimensional LowRank Tensor Autoregressive Time Series Modeling
Modern technological advances have enabled an unprecedented amount of st...
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KullbackLeiblerBased Discrete Relative Risk Models for Integration of Published Prediction Models with New Dataset
Existing literature for prediction of timetoevent data has primarily f...
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Third ArchEdge Workshop: Exploring the Design Space of Efficient Deep Neural Networks
This paper gives an overview of our ongoing work on the design space exp...
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Probabilistic ResourceAware Session Types
Session types guarantee that messagepassing processes adhere to predefi...
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Empirical Risk Minimization in the Noninteractive Local Model of Differential Privacy
In this paper, we study the Empirical Risk Minimization (ERM) problem in...
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Towards Latencyaware DNN Optimization with GPU Runtime Analysis and Tail Effect Elimination
Despite the superb performance of StateOfTheArt (SOTA) DNNs, the incr...
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Deep Learning Analysis and Age Prediction from Shoeprints
Human walking and gaits involve several complex body parts and are influ...
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Differentially Private (Gradient) Expectation Maximization Algorithm with Statistical Guarantees
(Gradient) Expectation Maximization (EM) is a widely used algorithm for ...
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On Differentially Private Stochastic Convex Optimization with Heavytailed Data
In this paper, we consider the problem of designing Differentially Priva...
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Robust High Dimensional Expectation Maximization Algorithm via Trimmed Hard Thresholding
In this paper, we study the problem of estimating latent variable models...
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Estimating Stochastic Linear Combination of Nonlinear Regressions Efficiently and Scalably
Recently, many machine learning and statistical models such as nonlinea...
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Learning Robust Algorithms for Online Allocation Problems Using Adversarial Training
We address the challenge of finding algorithms for online allocation (i....
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ECG Beats Fast Classification Base on Sparse Dictionaries
Feature extraction plays an important role in Electrocardiogram (ECG) Be...
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Bipartite Matching in Nearlylinear Time on Moderately Dense Graphs
We present an Õ(m+n^1.5)time randomized algorithm for maximum cardinali...
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AntiDote: Attentionbased Dynamic Optimization for Neural Network Runtime Efficiency
Convolutional Neural Networks (CNNs) achieved great cognitive performanc...
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Geno: A Developer Tool for Authoring Multimodal Interaction on Existing Web Applications
Supporting voice commands in applications presents significant benefits ...
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Liquid Resource Types
This article presents liquid resource types, a technique for automatical...
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Raising Expectations: Automating Expected Cost Analysis with Types
This article presents a typebased analysis for deriving upper bounds on...
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pNorm Flow Diffusion for Local Graph Clustering
Local graph clustering and the closely related seed set expansion proble...
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Towards Assessment of Randomized Mechanisms for Certifying Adversarial Robustness
As a certified defensive technique, randomized smoothing has received co...
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Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness
As a certified defensive technique, randomized smoothing has received co...
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Distributed Kernel Ridge Regression with Communications
This paper focuses on generalization performance analysis for distribute...
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Tail Bound Analysis for Probabilistic Programs via Central Moments
For probabilistic programs, it is usually not possible to automatically ...
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Robust FeatureBased Point Registration Using Directional Mixture Model
This paper presents a robust probabilistic point registration method for...
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Unsupervised Domain Adaptation for Object Detection via CrossDomain SemiSupervised Learning
Current stateoftheart object detectors can have significant performan...
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Facility Location Problem in Differential Privacy Model Revisited
In this paper we study the uncapacitated facility location problem in th...
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Flowless: Extracting Densest Subgraphs Without Flow Computations
We propose a simple and computationally efficient method for dense subgr...
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Estimating Smooth GLM in Noninteractive Local Differential Privacy Model with Public Unlabeled Data
In this paper, we study the problem of estimating smooth Generalized Lin...
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INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps
Behaviorrelated research areas such as motion prediction/planning, repr...
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Faster widthdependent algorithm for mixed packing and covering LPs
In this paper, we give a faster widthdependent algorithm for mixed pack...
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KnowledgeEnriched Transformer for Emotion Detection in Textual Conversations
Messages in human conversations inherently convey emotions. The task of ...
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Heterogeneous Graph Convolutional Networks for Temporal Community Detection
The Graph Convolutional Networks (GCN) has demonstrated superior perform...
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Highdimensional vector autoregressive time series modeling via tensor decomposition
The classical vector autoregressive model is a fundamental tool for mult...
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Distributed Equivalent Substitution Training for LargeScale Recommender Systems
We present Distributed Equivalent Substitution (DES) training, a novel d...
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Compact Autoregressive Network
Autoregressive networks can achieve promising performance in many sequen...
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Scalable Topological Data Analysis and Visualization for Evaluating DataDriven Models in Scientific Applications
With the rapid adoption of machine learning techniques for largescale a...
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EEGBased Emotion Recognition Using Regularized Graph Neural Networks
In this paper, we propose a regularized graph neural network (RGNN) for ...
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SinglePath Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization
Can we reduce the search cost of Neural Architecture Search (NAS) from d...
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Flows in Almost Linear Time via Adaptive Preconditioning
We present algorithms for solving a large class of flow and regression p...
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Neural Learning of Online Consumer Credit Risk
This paper takes a deep learning approach to understand consumer credit ...
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SinglePath NAS: DeviceAware Efficient ConvNet Design
Can we automatically design a Convolutional Network (ConvNet) with the h...
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ResourceGuided Program Synthesis
This article presents resourceguided synthesis, a technique for synthes...
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SinglePath NAS: Designing HardwareEfficient ConvNets in less than 4 Hours
Can we automatically design a Convolutional Network (ConvNet) with the h...
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Density Matching for Bilingual Word Embedding
Recent approaches to crosslingual word embedding have generally been ba...
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Differentially Private High Dimensional Sparse Covariance Matrix Estimation
In this paper, we study the problem of estimating the covariance matrix ...
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Expander Decomposition and Pruning: Faster, Stronger, and Simpler
We study the problem of graph clustering where the goal is to partition ...
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