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10/04/2022
Data drift correction via time-varying importance weight estimator
Real-world deployment of machine learning models is challenging when dat...
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12/10/2021
Deep Q-Network with Proximal Iteration
We employ Proximal Iteration for value-function optimization in reinforc...
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11/04/2021
Benchmarking Multimodal AutoML for Tabular Data with Text Fields
We consider the use of automated supervised learning systems for data ta...
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10/26/2021
Deep Explicit Duration Switching Models for Time Series
Many complex time series can be effectively subdivided into distinct reg...
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06/21/2021
Dive into Deep Learning
This open-source book represents our attempt to make deep learning appro...
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03/17/2021
IRLI: Iterative Re-partitioning for Learning to Index
Neural models have transformed the fundamental information retrieval pro...
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02/26/2021
Deep Quantile Aggregation
Conditional quantile estimation is a key statistical learning challenge ...
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02/18/2021
Continuous Doubly Constrained Batch Reinforcement Learning
Reliant on too many experiments to learn good actions, current Reinforce...
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06/26/2020
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning
This paper prescribes a suite of techniques for off-policy Reinforcement...
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06/25/2020
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
Automated machine learning (AutoML) can produce complex model ensembles ...
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04/06/2020
TraDE: Transformers for Density Estimation
We present TraDE, an attention-based architecture for auto-regressive de...
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02/14/2020
Transformer on a Diet
Transformer has been widely used thanks to its ability to capture sequen...
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09/30/2019
Meta-Q-Learning
This paper introduces Meta-Q-Learning (MQL), a new off-policy algorithm ...
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05/05/2019
P3O: Policy-on Policy-off Policy Optimization
On-policy reinforcement learning (RL) algorithms have high sample comple...
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04/20/2019
Language Models with Transformers
The Transformer architecture is superior to RNN-based models in computat...
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12/02/2017
Compressed Video Action Recognition
Training robust deep video representations has proven to be much more ch...
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11/30/2017
State Space LSTM Models with Particle MCMC Inference
Long Short-Term Memory (LSTM) is one of the most powerful sequence model...
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09/12/2017
Variational Reasoning for Question Answering with Knowledge Graph
Knowledge graph (KG) is known to be helpful for the task of question ans...
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09/05/2017
A Generic Approach for Escaping Saddle points
A central challenge to using first-order methods for optimizing nonconve...
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06/23/2017
Sampling Matters in Deep Embedding Learning
Deep embeddings answer one simple question: How similar are two images? ...
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03/31/2017
Spectral Methods for Nonparametric Models
Nonparametric models are versatile, albeit computationally expensive, to...
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02/27/2017
HashBox: Hash Hierarchical Segmentation exploiting Bounding Box Object Detection
We propose a novel approach to address the Simultaneous Detection and Se...
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12/06/2015
Explaining reviews and ratings with PACO: Poisson Additive Co-Clustering
Understanding a user's motivations provides valuable information beyond ...
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08/20/2015
AdaDelay: Delay Adaptive Distributed Stochastic Convex Optimization
We study distributed stochastic convex optimization under the delayed gr...
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05/18/2015
Graph Partitioning via Parallel Submodular Approximation to Accelerate Distributed Machine Learning
Distributed computing excels at processing large scale data, but the com...
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05/06/2015
Fast Differentially Private Matrix Factorization
Differentially private collaborative filtering is a challenging task, bo...
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12/31/2014
ACCAMS: Additive Co-Clustering to Approximate Matrices Succinctly
Matrix completion and approximation are popular tools to capture a user'...
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12/19/2014
A la Carte - Learning Fast Kernels
Kernel methods have great promise for learning rich statistical represen...
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09/21/2008