Lecida Reading Group

The Lecida Reading Group meets weekly to discuss papers in machine learning, deep learning, and distributed systems. If you're interested in attending or would like to know more, please get in touch.

Date Title
Feb 8, 2019 Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization
Jan 18, 2019 Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift
Dec 14, 2018 MADE: Masked Autoencoder for Distribution Estimation
Nov 30, 2018 Bigtable: A Distributed Storage System for Structured Data
Nov 16, 2018 A Deep and Tractable Density Estimator
Nov 9, 2018 Multivariate Time Series Classification Using Dynamic Time Warping Template Selection for Human Activity Recognition
Oct 19, 2018 Supervised learning from incomplete data via an EM approach
Oct 12, 2018 Snorkel: Rapid Training Data Creation with Weak Supervision
Oct 05, 2018 Mixtures of Sparse Autoregressive Networks
Sep 28, 2018 Structured Streaming: A Declarative API for Real-Time Applications in Apache Spark
Sep 14, 2018 RNADE: The real-valued neural autoregressive density-estimator
Aug 31, 2018 Algebraic Data Types, Monads, and Monad Combinators
Aug 17, 2018 Learning from Delayed Outcomes with Intermediate Observations
Jul 30, 2018 DROP: Dimensionality Reduction Optimization for Time Series
Jul 20, 2018 KerA: Scalable Data Ingestion for Stream Processing
Jul 13, 2018 Twin Networks: Matching the Future for Sequence Generation
Jul 6, 2018 Task-based End-to-end Model Learning in Stochastic Optimization
Jun 29, 2018 Highly Available Transactions: Virtues and Limitations
Jun 22, 2018 Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
Jun 14, 2018 Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases
May 11, 2018 Deep Learning for Automated Drivetrain Fault Detection
May 4, 2018 Dropout as a Bayesian Approximation
Apr 27, 2018 Building Cloud Infrastructure
Apr 13, 2018 Time Series Shapelets: A New Primitive for Data Mining
Apr 6, 2018 Predictive State Decoders
Mar 23, 2018 Novelty Detection with Multivariate Extreme Value Statistics
Mar 9, 2018 Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
Mar 2, 2018 Real-Time Anomaly Detection for Streaming Analytics
Feb 23, 2018 Improving Multi-step Prediction of Learned Time Series Models
Feb 16, 2018 Deep Survival Analysis
Feb 2, 2018 iSAX 2.0: Indexing and Mining One Billion Time Series
Jan 26, 2018 Clipper: A Low-Latency Online Prediction Serving System
Dec 13, 2017 Adversarial Discriminative Domain Adaptation
Nov 8, 2017 ZooKeeper: Wait-free coordination for Internet-scale systems
Oct 20, 2017 Understanding Black-box Predictions via Influence Functions
Oct 13, 2017 Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
Oct 6, 2017 SMASH: One-Shot Model Architecture Search through HyperNetworks
Sep 15, 2017 Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs
Sep 8, 2017 "Why Should I Trust You?": Explaining the Predictions of Any Classifier
Sep 1, 2017 WTTE-RNN: Weibull Time To Event Recurrent Neural Network
Aug 25, 2017 Weld: A Common Runtime for High Performance Data Analytics
Aug 4, 2017 Attention Is All You Need
Jul 28, 2017 Logistic Regression in Rare Events Data
Jul 14, 2017 Bring Your Own Learner: A Cloud-Based, Data-Parallel Commons for Machine Learning
Jun 30, 2017 Linux Containers
Jun 23, 2017 Particle filters for remaining useful life estimation of abatement equipment used in semiconductor manufacturing
Jun 16, 2017 Chord: A Scalable Peer-to-peer Lookup Protocol for Internet Applications
Jun 9, 2017 Machine Learning for Predictive Maintenance: A Multiple Classifier Approach
May 26, 2017 Understanding deep learning requires rethinking generalization
May 12, 2017 WaveNet: A Generative Model for Raw Audio
Apr 28, 2017 The Google File System
Mar 17, 2017 Static and dynamic novelty detection methods for jet engine health monitoring
Mar 3, 2017 Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Feb 10, 2017 What’s your ML test score? A rubric for ML production systems
Feb 3, 2017 Neural Architecture Search with Reinforcement Learning
Jan 20, 2017 Recurrent Highway Networks
Dec 9, 2016 Visualizing Data using t-SNE
Dec 2, 2016 Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
Nov 11, 2016 A Clockwork RNN
Oct 21, 2016 Bishop: MCMC and Gibbs Sampling
Oct 14, 2016 Bishop: Sampling Methods
Sep 23, 2016 Generating Sequences With Recurrent Neural Networks
Sep 16, 2016 Stream Computing
Sep 9, 2016 Connectionist Temporal Classification
Sep 2, 2016 MacroBase: Prioritizing Attention in Fast Data
Aug 26, 2016 Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing
Aug 19, 2016 Distilling the Knowledge in a Neural Network
Aug 12, 2016 Analysis of Hidden Markov Models and Support Vector Machines in Financial Applications
Aug 5, 2016 Neural Machine Translation by Jointly Learning to Align and Translate
Jul 29, 2016 MapReduce: Simplified Data Processing on Large Clusters
Jul 22, 2016 Recurrent Neural Networks for Multivariate Time Series with Missing Values
Jul 15, 2016 LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection