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06/21/2023
Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms
In stochastic zeroth-order optimization, a problem of practical relevanc...
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06/13/2023
Contextual Dictionary Lookup for Knowledge Graph Completion
Knowledge graph completion (KGC) aims to solve the incompleteness of kno...
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06/02/2023
Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation
NMT systems trained on Pre-trained Multilingual Sequence-Sequence (PMSS)...
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01/01/2023
Optimization of Image Transmission in a Cooperative Semantic Communication Networks
In this paper, a semantic communication framework for image transmission...
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11/30/2022
xTrimoABFold: Improving Antibody Structure Prediction without Multiple Sequence Alignments
In the field of antibody engineering, an essential task is to design a n...
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10/11/2022
On Adaptivity in Non-stationary Stochastic Optimization With Bandit Feedback
In this paper we study the non-stationary stochastic optimization questi...
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09/16/2022
Detecting Political Biases of Named Entities and Hashtags on Twitter
Ideological divisions in the United States have become increasingly prom...
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08/17/2022
Performance Optimization for Semantic Communications: An Attention-based Reinforcement Learning Approach
In this paper, a semantic communication framework is proposed for textua...
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07/22/2022
Fairness-aware Network Revenue Management with Demand Learning
In addition to maximizing the total revenue, decision-makers in lots of ...
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09/10/2021
Differential Privacy in Personalized Pricing with Nonparametric Demand Models
In the recent decades, the advance of information technology and abundan...
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01/29/2021
Meta-Reinforcement Learning for Reliable Communication in THz/VLC Wireless VR Networks
In this paper, the problem of enhancing the quality of virtual reality (...
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01/05/2021
Adversarial Combinatorial Bandits with General Non-linear Reward Functions
In this paper we study the adversarial combinatorial bandit with a known...
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12/11/2020
Smooth Bandit Optimization: Generalization to Hölder Space
We consider bandit optimization of a smooth reward function, where the g...
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09/27/2020
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning
The prevalence of e-commerce has made detailed customers' personal infor...
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09/07/2020
Nearly Bounded Regret of Re-solving Heuristics in Price-based Revenue Management
Price-based revenue management is a class of important questions in oper...
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09/04/2020
Nearly Dimension-Independent Sparse Linear Bandit over Small Action Spaces via Best Subset Selection
We consider the stochastic contextual bandit problem under the high dime...
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03/16/2020
Uncertainty Quantification for Demand Prediction in Contextual Dynamic Pricing
Data-driven sequential decision has found a wide range of applications i...
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12/09/2019
Optimism in Reinforcement Learning with Generalized Linear Function Approximation
We design a new provably efficient algorithm for episodic reinforcement ...
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10/09/2019
Robust Dynamic Assortment Optimization in the Presence of Outlier Customers
We consider the dynamic assortment optimization problem under the multin...
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09/17/2019
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...
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09/05/2019
√(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...
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08/31/2019
NCLS: Neural Cross-Lingual Summarization
Cross-lingual summarization (CLS) is the task to produce a summary in on...
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05/04/2019
Tight Regret Bounds for Infinite-armed Linear Contextual Bandits
Linear contextual bandit is a class of sequential decision making proble...
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03/30/2019
Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits
We study the linear contextual bandit problem with finite action sets. W...
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02/07/2019
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...
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10/31/2018
Dynamic Assortment Optimization with Changing Contextual Information
In this paper, we study the dynamic assortment optimization problem unde...
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10/25/2018
Efficient Load Sampling for Worst-Case Structural Analysis Under Force Location Uncertainty
An important task in structural design is to quantify the structural per...
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06/27/2018
Dynamic Assortment Selection under the Nested Logit Models
We study a stylized dynamic assortment planning problem during a selling...
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05/26/2018
Robust Nonparametric Regression under Huber's ε-contamination Model
We consider the non-parametric regression problem under Huber's ϵ-contam...
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05/25/2018
Phrase Table as Recommendation Memory for Neural Machine Translation
Neural Machine Translation (NMT) has drawn much attention due to its pro...
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05/21/2018
How Many Samples are Needed to Learn a Convolutional Neural Network?
A widespread folklore for explaining the success of convolutional neural...
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05/12/2018
Near-Optimal Policies for Dynamic Multinomial Logit Assortment Selection Models
In this paper we consider the dynamic assortment selection problem under...
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03/22/2018
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates
We consider the problem of global optimization of an unknown non-convex ...
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02/26/2018
Near-Linear Time Local Polynomial Nonparametric Estimation
Local polynomial regression (Fan & Gijbels, 1996) is an important class ...
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02/21/2018
Direct Learning to Rank and Rerank
Learning-to-rank techniques have proven to be extremely useful for prior...
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11/14/2017
Near-Optimal Discrete Optimization for Experimental Design: A Regret Minimization Approach
The experimental design problem concerns the selection of k points from ...
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11/13/2017
Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT
Neural machine translation (NMT), a new approach to machine translation,...
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11/03/2017
Towards Neural Machine Translation with Partially Aligned Corpora
While neural machine translation (NMT) has become the new paradigm, the ...
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10/30/2017
Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions
In this paper we study the frequentist convergence rate for the Latent D...
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10/29/2017
Stochastic Zeroth-order Optimization in High Dimensions
We consider the problem of optimizing a high-dimensional convex function...
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09/18/2017
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 ...
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08/09/2017
Non-stationary Stochastic Optimization with Local Spatial and Temporal Changes
We consider a non-stationary sequential stochastic optimization problem,...
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02/24/2017
Sequence Modeling via Segmentations
Segmental structure is a common pattern in many types of sequences such ...
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02/22/2017
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...
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02/09/2017
Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates
Although a majority of the theoretical literature in high-dimensional st...
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10/24/2016
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data
Subspace clustering is the problem of partitioning unlabeled data points...
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06/20/2016
Online and Differentially-Private Tensor Decomposition
In this paper, we resolve many of the key algorithmic questions regardin...
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02/23/2016
An Improved Gap-Dependency Analysis of the Noisy Power Method
We consider the noisy power method algorithm, which has wide application...
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02/19/2016
Spectral Learning for Supervised Topic Models
Supervised topic models simultaneously model the latent topic structure ...
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01/09/2016
