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Machine Learning and Friends Lunch

About

This semester of the UMass Machine Learning and Friends Lunch (MLFL) series has been graciously sponsored by our friends at Oracle Labs. 

MLFL is a lively and interactive forum held weekly where friends of the UMass Amherst machine learning community can sit down, have lunch, and give or hear a 50-minute presentation on recent machine learning research.

What is it?   A gathering of students/faculty/staff with broad interest in the methods and applications of machine learning.
When is it?    Thursdays 12:00pm to 1:00pm, unless otherwise noted. Arrive at 11:45 to get pizza.
Where is it?    CS150
Who is invited?   Everyone is welcome.
Is there food?    Yes! Pizza is provided.
Can I present?    Yes! If you would like to present your research, please email one of the organizers: Ari Kobren, Rajarshi Das, Hang Su, Samer Nashed and Aruni Roy Chowdhury

 

Recent Talks

April 18, 2019 Dylan Foster - Logistic Regression: The Importance of Being Improper
April 11, 2019 Christoph Riedl - Quantifying Reputation and Success in Art
April 4, 2019 Alexander Rush - Controllable Text Generation with Deep Latent-Variable Models
April 2, 2019 Swabha Swayampdipta - Learning Challenges in Natural Language Processing
March 28, 2019 Ishan Misra - Scaling Self-supervised Visual Representation Learning
March 7, 2019 Alex Gittens - Intelligent Randomized Algorithms for the Low CP-Rank Tensor Approximation Problem
February 28, 2019 Farhad Pourkamali Anaraki - Scalable and Robust Sparse Subspace Clustering
February 21, 2019 Irene Chen - Why is my classifier discriminatory?
February 14, 2019 Patrick Verga - Neural Knowledge Representation And Reasoning
February 7, 2019 Alane Suhr - Modeling and Learning Agents that Understand Language in Context
January 31, 2019 Sarah Adel Bargal - Grounding Deep Models of Visual Data
November 28, 2018 Alexandra Olteanu - Social Data Biases Methodological Pitfalls And Social Good Applications
November 8, 2018 Subhro Roy - Towards Natural Human Robot Communication
October 24, 2018 Ellie Pavlick - Why should we care about linguistics?
October 18, 2018 Noémie Elhadad
October 11, 2018 Fredrik Johansson
October 4, 2018 Jun-Yan Zhu - Learning to Generate Images
September 27, 2018 Anna Rogers - What's in your embedding, and how it predicts task performance.
September 20, 2018 Maggie Makar - Spread of Contagions in the Presence of Latent Spreaders
September 13, 2018 Liping Liu - Embedding: Choose Right Relations to Embed

2017/2018 Academic Year

April 26, 2018 Robot Perception For Manipulation - Peter Yu
April 19, 2018 Bridging Probabilistic Inference And Motion Planning With Markov Chain Monte Carlo - Daqing Yi
April 10, 2018 Insights from Deep Representations - Maithra Raghu
March 29, 2018 Exponential Family Embeddings - Maja Rudolph
March 22, 2018 New and Old Concentration Inequalities - Philip Thomas
March 8, 2018 CANCELLED - Jerry Li
March 1, 2018 Yulia Tsvetkov
February 22, 2018 Joseph Tassarotti - Hashing and Sketching for Latent Dirichlet-Categorical Models
February 15, 2018 Adji Dieng - Deep Sequence Models: Context Representation, Regularization, and Application to Language.
February 8, 2018 Bharath Hariharan - Visual recognition beyond large labeled training sets
February 1, 2018 Graham Neubig - What Can Neural Networks Teach us about Language?
November 30, 2017 Rajesh Ranganath - Black Box Variational Inference: Scalable, Generic Bayesian Computation and its Applications
November 20, 2017 Claudia Pérez D’Arpino - Learning How to Plan for Multi-Step Manipulation in Collaborative Robotics
November 16, 2017 Steven Wu - A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem
November 9, 2017 What Makes a Good Argument? Understanding and Predicting High Quality Arguments Using NLP Methods
November 2, 2017 Beomjoon Kim - Learning to Guide Task and Motion Planning by Predicting Constraints
October 26, 2017 Claudia Pérez D'Arpino
October 12, 2017 Varun Jampani - Bilateral Neural Networks for Image,Video and 3D Vision
October 5, 2017 Francesco Orabona - Coin Betting For Backprop Without Learning Rates And More
September 28, 2017 Nika Haghtalab - Oracle-efficient Online Learning And Applications To Auction Design
September 21, 2017 Yogarshi Vyas - Detecting Asymmetric Semantic Relations in Context : A Case-Study on Hypernymy Detection
September 14, 2017 Pat Flaherty - A Nonparametric Bayesian Model for Single-cell Variant Calling
September 7, 2017 Dean Eckles

2016/2017 Academic Year

June 13, 2017 Qiang Liu - A Stein Variational Framework for Deep Probabilistic Modeling
May 4, 2017 Scott W. Linderman - Bayesian Learning and Inference in Recurrent Switching Linear Dynamical Systems
April 26, 2017 Tom Williams - Genuine Helpers: Enabling Natural Language Capabilities for Interactive Robots
April 20, 2017 Hari Balasubramanian - Models Based on Longitudinal Healthcare Event Data
April 13, 2017 Sainbayar Sukhbaatar - Intrinsic Motivation And Automatic Curricula Via Asymmetric Self-Play
April 6, 2017 Robert Kozma - Computational Aspects of Brain Dynamics: Experiments, Models, and New AI Approaches
March 30, 2017 Mikael Henaff - Tracking The World State With Recurrent Entity Networks
March 23, 2017 David Moorman - Making Sense of Neuron Ensembles: Advances and Issues in Neural Coding
February 23, 2017 Andrew Trapp - Using Density To Identify Fixations In Gaze Data Optimization-Based Formulations And Algorithms
February 16, 2017 Naomi Fitter - Exploring Human-Inspired Haptic Interaction Skills For Robots
February 14, 2017 Tsendsuren Munkhdalai - Language Understanding And Reasoning With Memory Augmented Neural Networks
February 9, 2017 Hao Tang - Sequence Prediction With Neural Segmental Models
February 2, 2017 Stephan Mandt - Advances In Scalable Probabilistic Modeling Theory Applications And Challenges
January 19, 2017 Jeff Flanigan - Parsing And Generation For The Abstract Meaning Representation
December 8, 2016 John Lalor - Building Evaluation Scales For NLP Using Item Response Theory
December 1, 2016 Jayant Krishnamurthy - Semantic Parsing To Probabilistic Programs For Situated Question Answering
November 30, 2016 Mohit Iyyer, University of Maryland
November 30, 2016 Pegram Rooshenas - Learning Tractable Graphical Models
November 17, 2016 Andreas ten Pas - Grasp Pose Detection In Dense Clutter
November 10, 2016 Evan Shelhamer - A Fuller Understanding Of Fully Convolutional Networks
November 10, 2016 Samantha Kleinberg - Causal Inference and Explanation to Improve Human Health
November 3, 2016 Tianan Xue - Visual Dynamics Probabilistic Future Frame Synthesis Via Cross Convolutional Networks
October 27, 2016 Chris Kedzie, Real-Time Web Scale Event Summarization Using Sequential Decision Making
October 20, 2016 Jiajun Wu - Computational Perception of Physical Object Properties
October 13, 2016 Hugo Larochelle - Fighting our Big Data Addiction with Representation Learning
October 11, 2016 Chao Chen - Topological Analysis of Modern Data
September 22, 2016 Thien Nyugen - Neural Information Extraction with Memory
September 16, 2016 Siva Reddy - Freebase Semantic Parsing With And Without QA Pairs
September 15, 2016 Antoine Bordes - Reasoning With Memory Networks Successes And Challenges

 

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