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11/01/2022
Preserving In-Context Learning ability in Large Language Model Fine-tuning
Pretrained large language models (LLMs) are strong in-context learners t...
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10/16/2022
End-to-End Learning to Index and Search in Large Output Spaces
Extreme multi-label classification (XMC) is a popular framework for solv...
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06/22/2022
FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor Search
Approximate K-Nearest Neighbor Search (AKNNS) has now become ubiquitous ...
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04/22/2022
Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion
Conventional methods for query autocompletion aim to predict which compl...
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02/24/2022
Sample Efficiency of Data Augmentation Consistency Regularization
Data augmentation is popular in the training of large neural networks; c...
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10/29/2021
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
Learning on graphs has attracted significant attention in the learning c...
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10/01/2021
Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification
Extreme multi-label text classification (XMC) seeks to find relevant lab...
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06/24/2021
Label Disentanglement in Partition-based Extreme Multilabel Classification
Partition-based methods are increasingly-used in extreme multi-label cla...
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06/23/2021
Extreme Multi-label Learning for Semantic Matching in Product Search
We consider the problem of semantic matching in product search: given a ...
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06/16/2021
Robust Training in High Dimensions via Block Coordinate Geometric Median Descent
Geometric median (Gm) is a classical method in statistics for achieving ...
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06/13/2021
DP-NormFedAvg: Normalizing Client Updates for Privacy-Preserving Federated Learning
In this paper, we focus on facilitating differentially private quantized...
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06/01/2021
Enabling Efficiency-Precision Trade-offs for Label Trees in Extreme Classification
Extreme multi-label classification (XMC) aims to learn a model that can ...
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03/03/2021
Combinatorial Bandits without Total Order for Arms
We consider the combinatorial bandits problem, where at each time step, ...
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03/03/2021
Linear Bandit Algorithms with Sublinear Time Complexity
We propose to accelerate existing linear bandit algorithms to achieve pe...
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12/09/2020
Session-Aware Query Auto-completion using Extreme Multi-label Ranking
Query auto-completion is a fundamental feature in search engines where t...
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12/07/2020
Improved Convergence Rates for Non-Convex Federated Learning with Compression
Federated learning is a new distributed learning paradigm that enables e...
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10/12/2020
PECOS: Prediction for Enormous and Correlated Output Spaces
Many challenging problems in modern applications amount to finding relev...
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04/24/2020
Non-Exhaustive, Overlapping Co-Clustering: An Extended Analysis
The goal of co-clustering is to simultaneously identify a clustering of ...
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08/27/2019
Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure
The architecture of Transformer is based entirely on self-attention, and...
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06/18/2019
Inverting Deep Generative models, One layer at a time
We study the problem of inverting a deep generative model with ReLU acti...
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06/06/2019
Primal-Dual Block Frank-Wolfe
We propose a variant of the Frank-Wolfe algorithm for solving a class of...
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05/08/2019
AutoAssist: A Framework to Accelerate Training of Deep Neural Networks
Deep neural networks have yielded superior performance in many applicati...
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03/29/2019
SysML: The New Frontier of Machine Learning Systems
Machine learning (ML) techniques are enjoying rapidly increasing adoptio...
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01/15/2019
The Limitations of Adversarial Training and the Blind-Spot Attack
The adversarial training procedure proposed by Madry et al. (2018) is on...
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12/01/2018
Discrete Attacks and Submodular Optimization with Applications to Text Classification
Adversarial examples are carefully constructed modifications to an input...
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05/26/2018
Nonlinear Inductive Matrix Completion based on One-layer Neural Networks
The goal of a recommendation system is to predict the interest of a user...
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04/25/2018
Towards Fast Computation of Certified Robustness for ReLU Networks
Verifying the robustness property of a general Rectified Linear Unit (Re...
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03/25/2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization
Vanishing and exploding gradients are two of the main obstacles in train...
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03/17/2018
Learning Long Term Dependencies via Fourier Recurrent Units
It is a known fact that training recurrent neural networks for tasks tha...
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11/08/2017
Learning Non-overlapping Convolutional Neural Networks with Multiple Kernels
In this paper, we consider parameter recovery for non-overlapping convol...
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06/10/2017
Recovery Guarantees for One-hidden-layer Neural Networks
In this paper, we consider regression problems with one-hidden-layer neu...
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02/12/2017
Similarity Preserving Representation Learning for Time Series Analysis
A considerable amount of machine learning algorithms take instance-featu...
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06/02/2016
Generalized Root Models: Beyond Pairwise Graphical Models for Univariate Exponential Families
We present a novel k-way high-dimensional graphical model called the Gen...
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05/31/2016
Extreme Stochastic Variational Inference: Distributed and Asynchronous
We propose extreme stochastic variational inference (ESVI), an asynchron...
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03/11/2016
Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies
We develop Square Root Graphical Models (SQR), a novel class of parametr...
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09/28/2015
High-dimensional Time Series Prediction with Missing Values
High-dimensional time series prediction is needed in applications as div...
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05/07/2015
Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics
We provide a general theoretical analysis of expected out-of-sample util...
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11/22/2014
PU Learning for Matrix Completion
In this paper, we consider the matrix completion problem when the observ...
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06/27/2014
Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators
We consider the class of optimization problems arising from computationa...
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06/13/2013
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation
The L1-regularized Gaussian maximum likelihood estimator (MLE) has been ...
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06/04/2013
Provable Inductive Matrix Completion
Consider a movie recommendation system where apart from the ratings info...
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06/14/2011
Orthogonal Matching Pursuit with Replacement
In this paper, we consider the problem of compressed sensing where the g...
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10/30/2009