
PrivacyPreserving Dynamic Personalized Pricing with Demand Learning
The prevalence of ecommerce has made detailed customers' personal infor...
read it

Nearly Bounded Regret of Resolving Heuristics in Pricebased Revenue Management
Pricebased revenue management is a class of important questions in oper...
read it

Nearly DimensionIndependent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection
We consider the stochastic contextual bandit problem under the high dime...
read it

Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing
Datadriven sequential decision has found a wide range of applications i...
read it

Optimism in Reinforcement Learning with Generalized Linear Function Approximation
We design a new provably efficient algorithm for episodic reinforcement ...
read it

Robust Dynamic Assortment Optimization in the Presence of Outlier Customers
We consider the dynamic assortment optimization problem under the multin...
read it

Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs
In this paper, the problem of optimizing the deployment of unmanned aeri...
read it

√(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...
read it

NCLS: Neural CrossLingual Summarization
Crosslingual summarization (CLS) is the task to produce a summary in on...
read it

Tight Regret Bounds for Infinitearmed Linear Contextual Bandits
Linear contextual bandit is a class of sequential decision making proble...
read it

Nearly MinimaxOptimal Regret for Linearly Parameterized Bandits
We study the linear contextual bandit problem with finite action sets. W...
read it

On Asymptotically Tight Tail Bounds for Sums of Geometric and Exponential Random Variables
In this note we prove bounds on the upper and lower probability tails of...
read it

Dynamic Assortment Optimization with Changing Contextual Information
In this paper, we study the dynamic assortment optimization problem unde...
read it

Efficient Load Sampling for WorstCase Structural Analysis Under Force Location Uncertainty
An important task in structural design is to quantify the structural per...
read it

Dynamic Assortment Selection under the Nested Logit Models
We study a stylized dynamic assortment planning problem during a selling...
read it

Robust Nonparametric Regression under Huber's εcontamination Model
We consider the nonparametric regression problem under Huber's ϵcontam...
read it

Phrase Table as Recommendation Memory for Neural Machine Translation
Neural Machine Translation (NMT) has drawn much attention due to its pro...
read it

How Many Samples are Needed to Learn a Convolutional Neural Network?
A widespread folklore for explaining the success of convolutional neural...
read it

NearOptimal Policies for Dynamic Multinomial Logit Assortment Selection Models
In this paper we consider the dynamic assortment selection problem under...
read it

Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates
We consider the problem of global optimization of an unknown nonconvex ...
read it

NearLinear Time Local Polynomial Nonparametric Estimation
Local polynomial regression (Fan & Gijbels, 1996) is an important class ...
read it

Direct Learning to Rank and Rerank
Learningtorank techniques have proven to be extremely useful for prior...
read it

NearOptimal Discrete Optimization for Experimental Design: A Regret Minimization Approach
The experimental design problem concerns the selection of k points from ...
read it

Word, Subword or Character? An Empirical Study of Granularity in ChineseEnglish NMT
Neural machine translation (NMT), a new approach to machine translation,...
read it

Towards Neural Machine Translation with Partially Aligned Corpora
While neural machine translation (NMT) has become the new paradigm, the ...
read it

Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions
In this paper we study the frequentist convergence rate for the Latent D...
read it

Stochastic Zerothorder Optimization in High Dimensions
We consider the problem of optimizing a highdimensional convex function...
read it

A Note on Tight Lower Bound for MNLBandit Assortment Selection Models
In this note we prove a tight lower bound for the MNLbandit assortment ...
read it

Nonstationary Stochastic Optimization with Local Spatial and Temporal Changes
We consider a nonstationary sequential stochastic optimization problem,...
read it

Sequence Modeling via Segmentations
Segmental structure is a common pattern in many types of sequences such ...
read it

On the Power of Truncated SVD for General Highrank Matrix Estimation Problems
We show that given an estimate A that is close to a general highrank po...
read it

Rate Optimal Estimation and Confidence Intervals for Highdimensional Regression with Missing Covariates
Although a majority of the theoretical literature in highdimensional st...
read it

A Theoretical Analysis of Noisy Sparse Subspace Clustering on DimensionalityReduced Data
Subspace clustering is the problem of partitioning unlabeled data points...
read it

Online and DifferentiallyPrivate Tensor Decomposition
In this paper, we resolve many of the key algorithmic questions regardin...
read it

An Improved GapDependency Analysis of the Noisy Power Method
We consider the noisy power method algorithm, which has wide application...
read it

Spectral Learning for Supervised Topic Models
Supervised topic models simultaneously model the latent topic structure ...
read it

On Computationally Tractable Selection of Experiments in MeasurementConstrained Regression Models
We derive computationally tractable methods to select a small subset of ...
read it

Fast and Guaranteed Tensor Decomposition via Sketching
Tensor CANDECOMP/PARAFAC (CP) decomposition has wide applications in sta...
read it

Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data
We consider the problem of matrix column subset selection, which selects...
read it

Graph Connectivity in Noisy Sparse Subspace Clustering
Subspace clustering is the problem of clustering data points into a unio...
read it

Noiseadaptive Marginbased Active Learning and Lower Bounds under Tsybakov Noise Condition
We present a simple noiserobust marginbased active learning algorithm ...
read it

A Theoretical Analysis of NDCG Type Ranking Measures
A central problem in ranking is to design a ranking measure for evaluati...
read it
Yining Wang
is this you? claim profile
PhD student, Machine Learning Department at Carnegie Mellon University