Yining Wang

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Carnegie Mellon University ∙ Peking University

PhD student, Machine Learning Department at Carnegie Mellon University

Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing

Data-driven sequential decision has found a wide range of applications i...
03/16/2020 ∙ by Xi Chen, et al. ∙ 17 ∙ share

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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...
09/17/2019 ∙ by Yining Wang, et al. ∙ 5 ∙ share

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√(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...
09/05/2019 ∙ by Kefan Dong, et al. ∙ 4 ∙ share

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Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions

In this paper we study the frequentist convergence rate for the Latent D...
10/30/2017 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Stochastic Zeroth-order Optimization in High Dimensions

We consider the problem of optimizing a high-dimensional convex function...
10/29/2017 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models

In this note we prove a tight lower bound for the MNL-bandit assortment ...
09/18/2017 ∙ by Xi Chen, et al. ∙ 0 ∙ share

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Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes

We consider a non-stationary sequential stochastic optimization problem,...
08/09/2017 ∙ by Xi Chen, et al. ∙ 0 ∙ share

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Sequence Modeling via Segmentations

Segmental structure is a common pattern in many types of sequences such ...
02/24/2017 ∙ by Chong Wang, et al. ∙ 0 ∙ share

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On the Power of Truncated SVD for General High-rank Matrix Estimation Problems

We show that given an estimate A that is close to a general high-rank po...
02/22/2017 ∙ by Simon S. Du, et al. ∙ 0 ∙ share

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Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates

Although a majority of the theoretical literature in high-dimensional st...
02/09/2017 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data

Subspace clustering is the problem of partitioning unlabeled data points...
10/24/2016 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Online and Differentially-Private Tensor Decomposition

In this paper, we resolve many of the key algorithmic questions regardin...
06/20/2016 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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An Improved Gap-Dependency Analysis of the Noisy Power Method

We consider the noisy power method algorithm, which has wide application...
02/23/2016 ∙ by Maria-Florina Balcan, et al. ∙ 0 ∙ share

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On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models

We derive computationally tractable methods to select a small subset of ...
01/09/2016 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Fast and Guaranteed Tensor Decomposition via Sketching

Tensor CANDECOMP/PARAFAC (CP) decomposition has wide applications in sta...
06/14/2015 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data

We consider the problem of matrix column subset selection, which selects...
05/17/2015 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Graph Connectivity in Noisy Sparse Subspace Clustering

Subspace clustering is the problem of clustering data points into a unio...
04/04/2015 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Noise-adaptive Margin-based Active Learning and Lower Bounds under Tsybakov Noise Condition

We present a simple noise-robust margin-based active learning algorithm ...
06/20/2014 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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A Theoretical Analysis of NDCG Type Ranking Measures

A central problem in ranking is to design a ranking measure for evaluati...
04/24/2013 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT

Neural machine translation (NMT), a new approach to machine translation,...
11/13/2017 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Towards Neural Machine Translation with Partially Aligned Corpora

While neural machine translation (NMT) has become the new paradigm, the ...
11/03/2017 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Spectral Learning for Supervised Topic Models

Supervised topic models simultaneously model the latent topic structure ...
02/19/2016 ∙ by Yong Ren, et al. ∙ 0 ∙ share

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Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models

In this paper we consider the dynamic assortment selection problem under...
05/12/2018 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach

The experimental design problem concerns the selection of k points from ...
11/14/2017 ∙ by Zeyuan Allen-Zhu, et al. ∙ 0 ∙ share

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How Many Samples are Needed to Learn a Convolutional Neural Network?

A widespread folklore for explaining the success of convolutional neural...
05/21/2018 ∙ by Simon S. Du, et al. ∙ 0 ∙ share

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Direct Learning to Rank and Rerank

Learning-to-rank techniques have proven to be extremely useful for prior...
02/21/2018 ∙ by Cynthia Rudin, et al. ∙ 0 ∙ share

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Phrase Table as Recommendation Memory for Neural Machine Translation

Neural Machine Translation (NMT) has drawn much attention due to its pro...
05/25/2018 ∙ by Yang Zhao, et al. ∙ 0 ∙ share

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Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates

We consider the problem of global optimization of an unknown non-convex ...
03/22/2018 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Dynamic Assortment Selection under the Nested Logit Models

We study a stylized dynamic assortment planning problem during a selling...
06/27/2018 ∙ by Xi Chen, et al. ∙ 0 ∙ share

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Robust Nonparametric Regression under Huber's ε-contamination Model

We consider the non-parametric regression problem under Huber's ϵ-contam...
05/26/2018 ∙ by Simon S. Du, et al. ∙ 0 ∙ share

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Near-Linear Time Local Polynomial Nonparametric Estimation

Local polynomial regression (Fan & Gijbels, 1996) is an important class ...
02/26/2018 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Dynamic Assortment Optimization with Changing Contextual Information

In this paper, we study the dynamic assortment optimization problem unde...
10/31/2018 ∙ by Xi Chen, et al. ∙ 0 ∙ share

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Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits

We study the linear contextual bandit problem with finite action sets. W...
03/30/2019 ∙ by Yingkai Li, et al. ∙ 0 ∙ share

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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...
02/07/2019 ∙ by Yaonan Jin, et al. ∙ 0 ∙ share

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Tight Regret Bounds for Infinite-armed Linear Contextual Bandits

Linear contextual bandit is a class of sequential decision making proble...
05/04/2019 ∙ by Yingkai Li, et al. ∙ 0 ∙ share

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Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty

An important task in structural design is to quantify the structural per...
10/25/2018 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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NCLS: Neural Cross-Lingual Summarization

Cross-lingual summarization (CLS) is the task to produce a summary in on...
08/31/2019 ∙ by Junnan Zhu, et al. ∙ 0 ∙ share

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Robust Dynamic Assortment Optimization in the Presence of Outlier Customers

We consider the dynamic assortment optimization problem under the multin...
10/09/2019 ∙ by Xi Chen, et al. ∙ 0 ∙ share

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Optimism in Reinforcement Learning with Generalized Linear Function Approximation

We design a new provably efficient algorithm for episodic reinforcement ...
12/09/2019 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Yining Wang

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