# AISTATS 2018 Poster Sessions

## Accepted papers

All accepted papers are available here.

## Poster Format

The poster board is 0.90m (wide) x 2.10m (high). We recommend **A0 portrait** as
the poster size. **Please make sure to bring the posters printed to Lanzarote as there are no onsite printing facilities available.**

## Poster Session 1 (April 9)

Poster 1: **Submodularity on Hypergraphs: From Sets to Sequences**

Marko
Mitrovic

Poster 2: **Regional Multi-Armed Bandits**

Cong
Shen

Poster 3: **On the challenges of learning with inference networks on sparse high-dimensional data**

Rahul
Krishnan

Poster 4: **Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis**

Luca
Ambrogioni

Poster 5: **Combinatorial Preconditioners for Proximal Algorithms on Graphs**

Thomas
Möllenhoff

Poster 6: **Near-Optimal Machine Teaching via Explanatory Teaching Sets**

Yuxin
Chen

Poster 7: **Factorized Recurrent Neural Architectures for Longer Range Dependence**

Francois
Belletti

Poster 8: **Nonparametric Preference Completion**

Julian
Katz-Samuels

Poster 9: **HONES: A Fast and Tuning-free Homotopy Method For Online Newton Step**

Yuting
Ye

Poster 10: **Robustness of classifiers to uniform \ell_p and Gaussian noise**

Alhussein
Fawzi

Poster 11: **Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD**

Sanghamitra
Dutta

Poster 12: **Comparison Based Learning from Weak Oracles**

Ehsan
Kazemi

Poster 13: **Teacher Improves Learning by Selecting a Training Subset**

Xiaojin
Zhu

Poster 14: **Probability–Revealing Samples**

Krzysztof
Onak

Poster 15: **Topic Compositional Neural Language Model**

Wenlin
Wang

Poster 16: **Reducing Crowdsourcing to Graphon Estimation Statistically**

Christina
Lee

Poster 17: **Nonparametric Bayesian sparse graph linear dynamical systems**

Mingyuan
Zhou

Poster 18: **Learning Structural Weight Uncertainty with Stein Gradient Flows**

Chunyuan
Li

Poster 19: **The Binary Space Partitioning-Tree Process**

Xuhui
Fan

Poster 20: **Robust Maximization of Non-Submodular Objectives**

Ilija
Bogunovic

Poster 21: **FLAG n’ FLARE: Fast Linearly-Coupled Adaptive Gradient Methods**

Fred
Roosta

Poster 22: **Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams**

Chris
Hickey

Poster 23: **Proximity Variational Inference**

Jaan
Altosaar

Poster 24: **An Analysis of Categorical Distributional Reinforcement Learning**

Mark
Rowland

Poster 25: **Parallel and Distributed MCMC via Shepherding Distributions**

Arkabandhu
Chowdhury

Poster 26: **Inference in Sparse Graphs with Pairwise Measurements and Side Information**

Dylan
Foster

Poster 27: **IHT dies hard: Provable accelerated Iterative Hard Thresholding**

Anastasios
Kyrillidis

Poster 28: **High-dimensional Bayesian optimization via additive models with overlapping groups**

Paul
Rolland

Poster 29: **Learning Hidden Quantum Markov Models**

Siddarth
Srinivasan

Poster 30: **On denoising noisy modulo 1 samples of a function**

Mihai
Cucuringu

Poster 31: **A Generic Approach for Escaping Saddle points**

Manzil
Zaheer

Poster 32: **Nonlinear Weighted Finite Automata**

Tianyu
Li

Poster 33: **Few-shot Generative Modelling with Generative Matching Networks**

Sergey
Bartunov

Poster 34: **A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop**

Yichen
Wang

Poster 35: **Personalized and Private Peer-to-Peer Machine Learning**

Aurélien
Bellet

Poster 36: **Matrix-normal models for fMRI analysis**

Michael
Shvartsman

Poster 37: **A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians**

Slobodan
Mitrovic

Poster 38: **One-shot Coresets: The Case of k-Clustering**

Olivier
Bachem

Poster 39: **Iterative Supervised Principal Components**

Juho
Piironen

Poster 40: **Cause-Effect Inference by Comparing Regression Errors**

Patrick
Bloebaum

Poster 41: **Graphical Models for Non-Negative Data Using Generalized Score Matching**

Shiqing
Yu

Poster 42: **Best arm identification in multi-armed bandits with delayed feedback**

Aditya
Grover

Poster 43: **Approximate Bayesian Computation with Kullback-Leibler Divergence as Data Discrepancy**

Bai
Jiang

Poster 44: **A Unified Dynamic Approach to Sparse Model Selection**

Chendi
Huang

Poster 45: **On Statistical Optimality of Variational Bayes**

Debdeep
Pati

Poster 46: **Stochastic algorithms for entropy-regularized optimal transport problems**

Brahim Khalil
Abid

Poster 47: **Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means**

Dennis
Forster

Poster 48: **Learning Generative Models with Sinkhorn Divergences**

Aude
Genevay

Poster 49: **Product Kernel Interpolation for Scalable Gaussian Processes**

Jacob
Gardner

Poster 50: **Solving lp-norm regularization with tensor kernels**

Saverio
Salzo

Poster 51: **Statistically Efficient Estimation for Non-Smooth Probability Densities**

Masaaki Imaizumi,
Takanori Maehara, Yuichi Yoshida

Poster 52: **Stochastic Zeroth-order Optimization in High Dimensions**

Yining Wang, Arindam Banerjee, Simon Du, Sivaraman Balakrishnan,
Aarti Singh

Poster 53: **Sparse Linear Isotonic Models**

Sheng Chen,
Arindam Banerjee

Poster 54: **Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs**

Lawrence Murray, Daniel Lundén, Jan Kudlicka, David Broman,
Thomas Schön

## Poster Session 2 (April 10)

Poster 1: **Structured Factored Inference for Probabilistic Programming**

Alison
OConnor

Poster 2: **Weighted Tensor Decomposition for Learning Latent Variables with Partial Data**

Omer
Gottesman

Poster 3: **Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach**

Satoshi
Hara

Poster 4: **Finding Global Optima in Nonconvex Stochastic Semidefinite Optimization with Variance Reduction**

Jinshan
ZENG

Poster 5: **Plug-in Estimators for Conditional Expectations and Probabilities**

Steffen
Grunewalder

Poster 6: **Policy Evaluation and Optimization with Continuous Treatments**

Nathan
Kallus

Poster 7: **Tensor Regression Meets Gaussian Processes**

Rose
Yu

Poster 8: **Robust Locally-Linear Controllable Embedding**

Ershad
Banijamali

Poster 9: **Data-Efficient Reinforcement Learning with \\Probabilistic Model Predictive Control**

Marc
Deisenroth

Poster 10: **Smooth and Sparse Optimal Transport**

Mathieu
Blondel

Poster 11: **The Power Mean Laplacian for Multilayer Graph Clustering**

Pedro
Mercado

Poster 12: **Gauged Mini-Bucket Elimination for Approximate Inference**

Adrian
Weller

Poster 13: **Variational Inference based on Robust Divergences**

Futoshi
Futami

Poster 14: **Benefits from Superposed Hawkes Processes**

Hongteng
Xu

Poster 15: **Boosting Variational Inference: an Optimization Perspective**

Francesco
Locatello

Poster 16: **Tree-based Bayesian Mixture Model for Competing Risks**

Alexis
Bellot

Poster 17: **Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures**

Tomi
Silander

Poster 18: **Conditional Gradient Method for Stochastic Submodular Maximization: Closing the Gap**

Aryan
Mokhtari

Poster 19: **Medoids in Almost-Linear Time via Multi-Armed Bandits**

David
Tse

Poster 20: **On the Truly Block Eigensolvers via First-Order Riemannian Optimization**

Zhiqiang
Xu

Poster 21: **Efficient Weight Learning in High-Dimensional Untied MLNs**

Khan Mohammad Al
Farabi

Poster 22: **Beating Monte Carlo Integration: a Nonasymptotic Study of Kernel Smoothing Methods**

Stephan
Clémençon

Poster 23: **On how complexity effects the stability of a predictor**

Joel
Ratsaby

Poster 24: **Contextual Bandits with Stochastic Experts**

Rajat
Sen

Poster 25: **Online Learning with Non-Convex Losses and Non-Stationary Regret**

Xiaobo
Li

Poster 26: **Non-parametric estimation of Jensen-Shannon Divergence in Generative Adversarial Network training**

Mathieu
Sinn

Poster 27: **Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure**

Beilun
Wang

Poster 28: **Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications**

Sijia
Liu

Poster 29: **Robust Vertex Enumeration for Convex Hulls in High Dimensions**

Pranjal
Awasthi

Poster 30: **Turing: Composable inference for probabilistic programming**

Hong
Ge

Poster 31: **Combinatorial Penalties: Which structures are preserved by convex relaxations?**

Marwa
El Halabi

Poster 32: **Metrics for Deep Generative Models**

Nutan
Chen

Poster 33: **Spectral Algorithms for Computing Fair Support Vector Machines**

Mahbod
Olfat

Poster 34: **Optimal Submodular Extensions for Marginal Estimation**

Pankaj
Pansari

Poster 35: **Iterative Spectral Method for Alternative Clustering**

Chieh
Wu

Poster 36: **Differentially Private Regression with Gaussian Processes**

Michael
Smith

Poster 37: **Reconstruction Risk of Convolutional Sparse Dictionary Learning**

Shashank
Singh

Poster 38: **Learning to Round for Discrete Labeling Problems**

Pritish
Mohapatra

Poster 39: **Direct Learning to Rank And Rerank**

Cynthia
Rudin

Poster 40: **Linear Stochastic Approximation: Constant Step-Size and Iterate Averaging**

Chandrashekar
Lakshmi-Narayanan

Poster 41: **Approximate ranking from pairwise comparisons**

Reinhard
Heckel

Poster 42: **Stochastic Multi-armed Bandits in Constant Space**

Ger
Yang

Poster 43: **Multi-objective Contextual Bandit Problem with Similarity Information**

Cem
Tekin

Poster 44: **Scalable Generalized Dynamic Topic Models**

Patrick
Jähnichen

Poster 45: **Growth-Optimal Portfolio Selection under CVaR Constraints**

Guy
Uziel

Poster 46: **Statistical Sparse Online Regression: A Diffusion Approximation Perspective**

Junchi
Li

Poster 47: **Combinatorial Semi-Bandits with Knapsacks**

Karthik Abinav Sankararaman,
Aleksandrs Slivkins

Poster 48: **Online Continuous Submodular Maximization**

Lin Chen, Hamed Hassani,
Amin Karbasi

Poster 49: **Convergence of Value Aggregation for Imitation Learning**

Ching-An Cheng,
Byron Boots

Poster 50: **Competing with Automata-based Expert Sequences**

Scott Yang,
Mehryar Mohri

Poster 51: **A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer **

Tianbao Yang, Zhe Li,
Lijun Zhang

Poster 52: **Learning linear structural equation models in polynomial time and sample complexity**

Asish Ghoshal,
Jean Honorio

Poster 53: **Consistent Algorithms for Classification under Complex Losses and Constraints**

Harikrishna
Narasimhan

Poster 54: **Subsampling for Ridge Regression via Regularized Volume Sampling**

Michal Derezinski,
Manfred Warmuth

## Poster Session 3 (April 10)

Poster 1: **Group invariance principles for causal generative models**

Michel
Besserve

Poster 2: **Learning Priors for Invariance**

Eric
Nalisnick

Poster 3: **Catalyst for Gradient-based Nonconvex Optimization**

Courtney
Paquette

Poster 4: **Dropout as a Low-Rank Regularizer for Matrix Factorization**

Jacopo
Cavazza

Poster 5: **Practical Bayesian optimization in the presence of outliers**

Ruben
Martinez-Cantin

Poster 6: **Fast generalization error bound of deep learning from a kernel perspective**

Taiji
Suzuki

Poster 7: **Asynchronous Doubly Stochastic Group Regularized Learning**

Bin
Gu

Poster 8: **The emergence of spectral universality in deep networks**

Jeffrey
Pennington

Poster 9: **Post Selection Inference with Kernels**

Makoto
Yamada

Poster 10: **Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information**

Jakob
Runge

Poster 11: **Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization**

Joong-Ho
Won

Poster 12: **SDCA-Powered Inexact Dual Augmented Lagrangian Method for Fast CRF Learning**

Xu
Hu

Poster 13: **Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models**

Hugh
Salimbeni

Poster 14: **Semi-Supervised Learning with Competitive Infection Models**

Nir
Rosenfeld

Poster 15: **Random Subspace with Trees for Feature Selection Under Memory Constraints**

Antonio
Sutera

Poster 16: **Bayesian Structure Learning for Dynamic Brain Connectivity**

Michael
Andersen

Poster 17: **Riemannian stochastic quasi-Newton algorithm with variance reduction and its convergence analysis**

Hiroyuki
Kasai

Poster 18: **Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling**

Hongyi
Ding

Poster 19: **Efficient Bandit Combinatorial Optimization Algorithm with Zero-suppressed Binary Decision Diagrams**

Shinsaku
Sakaue

Poster 20: **Online Boosting Algorithms for Multi-label Ranking**

Young Hun
Jung

Poster 21: **Guaranteed Sufficient Decrease for Stochastic Variance Reduced Gradient Optimization**

Fanhua
Shang

Poster 22: **Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms**

Chung-Yi
Lin

Poster 23: **Matrix completability analysis via graph k-connectivity**

Dehua
Cheng

Poster 24: **A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization**

Emanuel
Laude

Poster 25: **Reducing optimization to repeated classification**

Tatsunori
Hashimoto

Poster 26: **Online Ensemble Multi-kernel Learning Adaptive to Non-stationary and Adversarial Environments**

Tianyi
Chen

Poster 27: **Transfer Learning on fMRI Datasets**

Hejia
Zhang

Poster 28: **Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data**

William
Herlands

Poster 29: **Nearly second-order optimality of online joint detection and estimation via one-sample update schemes**

Yang
Cao

Poster 30: **Outlier Detection and Robust Estimation in Nonparametric Regression**

Weining
Shen

Poster 31: **Dimensionality Reduced $\ell^{0}$-Sparse Subspace Clustering**

Yingzhen
Yang

Poster 32: **Sum-Product-Quotient Networks**

Or
Sharir

Poster 33: **Nonlinear Structured Signal Estimation in High Dimensions via Iterative Hard Thresholding**

Zhuoran
Yang

Poster 34: **Efficient Bayesian Methods for Counting Processes in Partially Observable Environments**

Ferdian
Jovan

Poster 35: **Stochastic Three-Composite Convex Minimization with a Linear Operator**

Renbo
Zhao

Poster 36: **Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models**

Atsushi
Nitanda

Poster 37: **Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model**

Christos
Tzamos

Poster 38: **Kernel Conditional Exponential Family**

Michael
Arbel

Poster 39: **Achieving the time of 1-NN but the accuracy of k-NN**

Lirong
Xue

Poster 40: **Bayesian Approaches to Distribution Regression**

Ho Chung Leon
Law

Poster 41: **Nested CRP with Hawkes-Gaussian Processes**

Xi
Tan

Poster 42: **Mixed Membership Word Embeddings for Computational Social Science**

James
Foulds

Poster 43: **Learning Determinantal Point Processes in Sublinear Time**

Christophe
Dupuy

Poster 44: **Fully adaptive algorithm for pure exploration in linear bandits**

Liyuan
Xu

Poster 45: **Variational inference for the multi-armed contextual bandit**

Iñigo
Urteaga

Poster 46: **A Provable Algorithm for Learning Interpretable Scoring Systems**

Nataliya
Sokolovska

Poster 47: **An Optimization Approach to Learning Falling Rule Lists**

Chaofan
Chen

Poster 48: **Fast Threshold Tests for Detecting Discrimination**

Emma Pierson, Sam Corbett-Davies,
Sharad Goel

Poster 49: **Parallelised Bayesian Optimisation via Thompson Sampling**

Kirthevasan Kandasamy, Akshay Krishnamurthy,
Jeff Schneider, Barnabas Poczos

Poster 50: **Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition**

Pavel Izmailov, Dmitry Kropotov,
Alexander Novikov

Poster 51: **Factorial HMM with Collapsed Gibbs Sampling for optimizing long-term HIV Therapy**

Amit Gruber, Chen Yanover, Tal El-Hay, Yaara Goldschmidt, Anders Sönnerborg,
Vanni Borghi, Francesca Incardona

Poster 52: **Sketching for Kronecker Product Regression and P-splines**

Huaian Diao, Zhao Song,
Wen Sun, David Woodruff

Poster 53: **Towards Provable Learning of Polynomial Neural Networks Using Low-Rank Matrix Estimation**

Mohammadreza Soltani,
Chinmay Hegde

Poster 54: **Convergence diagnostics for stochastic gradient descent**

Jerry Chee,
Panos Toulis

Poster 55: **Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems**

Jason Ge

## Poster Session 4 (April 11)

Poster 1: **Optimal Cooperative Inference**

Scott Cheng-Hsin
Yang

Poster 2: **Human Interaction with Recommendation Systems**

Sven
Schmit

Poster 3: **Convex optimization over intersection of simple sets: improved convergence rate guarantees via exact penalty approach**

Achintya
Kundu

Poster 4: **Towards Memory-Friendly Deterministic Incremental Gradient Method**

Jiahao
Xie

Poster 5: **Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables**

Masaaki
Takada

Poster 6: **AdaGeo: Adaptive Geometric Learning for Optimization and Sampling**

Gabriele
Abbati

Poster 7: **Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method**

Mark
Eisen

Poster 8: **Labeled Graph Clustering via Projected Gradient Descent**

Shiau Hong
Lim

Poster 9: **Discriminative Learning of Prediction Intervals**

Nir
Rosenfeld

Poster 10: **Accelerated Stochastic Power Iteration**

Peng
Xu

Poster 11: **A Bayesian Nonparametric Method for Clustering Imputation and Forecasting in Multivariate Time Series**

FERAS
SAAD

Poster 12: **Bayesian Multi-label Learning with Sparse Features and Labels**

He
Zhao

Poster 13: **Robust Active Label Correction**

Christian
Igel

Poster 14: **Factor Analysis on a Graph**

Masayuki
Karasuyama

Poster 15: **Reparameterizing the Birkhoff Polytope for Variational Permutation Inference**

Gonzalo
Mena

Poster 16: **Provable Estimation of the Number of Blocks in Block Models**

BOWEI
YAN

Poster 17: **Batched Large-scale Bayesian Optimization in High-dimensional Spaces**

Zi
Wang

Poster 18: **Actor-Critic Fictitious Play in Simultaneous Move Multistage Games**

Julien
Perolat

Poster 19: **Online Regression with Partial Information: Generalization and Linear Projection**

Shinji
Ito

Poster 20: **Alpha-expansion is Exact on Stable Instances**

Hunter
Lang

Poster 21: **Adaptive Sampling for Clustered Ranking**

Sumeet
Katariya

Poster 22: **Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations**

Alan
Lazarus

Poster 23: This poster has been moved

Poster 24: **The Geometry of Random Features**

Adrian
Weller

Poster 25: **Symmetric Variational Autoencoder and Connections to Adversarial Learning**

Liqun
Chen

Poster 26: **Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity**

Asish
Ghoshal

Poster 27: **A Unified Framework for Nonconvex Low-Rank plus Sparse Matrix Recovery**

Xiao
Zhang

Poster 28: **Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation**

Penporn
Koanantakool

Poster 29: **Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms**

Pan
Xu

Poster 30: **On the Statistical Efficiency of Compositional Nonparametric Prediction**

Yixi
Xu

Poster 31: **Exploiting Strategy-Space Diversity for Batch Bayesian Optimization**

Sunil
Gupta

Poster 32: **Variational Rejection Sampling**

Aditya
Grover

Poster 33: **Why adaptively collected data have negative bias and how to correct for it.**

Xinkun
Nie

Poster 34: **Generalized Binary Search For Split-Neighborly Problems**

Stephen
Mussmann

Poster 35: **Scalable Hash-Based Estimation of Divergence Measures**

Morteza
Noshad Iranzad

Poster 36: **Semi-Supervised Prediction-Constrained Topic Models**

Michael
Hughes

Poster 37: **Crowdclustering with Partition Labels**

Junxiang
Chen

Poster 38: **Generalized Concomitant Multi-Task Lasso for sparse multimodal regression**

Mathurin
Massias

Poster 39: **Gradient Diversity: a Key Ingredient for Scalable Distributed Learning**

Dong
Yin

Poster 40: **Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond**

Heng
Guo

Poster 41: **Multi-view Metric Learning in Vector-valued Kernel Spaces**

Riikka
Huusari

Poster 42: **Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth**

Jussi
Viinikka

Poster 43: **Variational Sequential Monte Carlo**

Christian Naesseth,
Scott Linderman, Rajesh Ranganath

Poster 44: **VAE with a VampPrior**

Jakub Tomczak,
Max Welling

Poster 45: **Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes**

Hyunjik Kim
, Yee Whye Teh

Poster 46: **Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models**

Ardavan Saeedi, Matthew Hoffman, Matthew Hoffman, Stephen DiVerdi, Asma Ghandeharioun, Matthew Johnson,
Ryan Adams

Poster 47: **Random Warping Series: A Random Features Method for Time-Series Embedding**

Lingfei Wu, Ian En-Hsu Yen,
Jinfeng Yi, Fangli Xu, Qi Lei, Michael Witbrock

Poster 48: **Efficient and principled score estimation with Nyström kernel exponential families**

Dougal Sutherland, Heiko Strathmann,
Michael Arbel, Arthur Gretton

Poster 49: **Multi-scale Nystrom Method**

Woosang Lim, Rundong Du, Bo Dai,
Kyomin Jung, Le Song

Poster 50: **Batch-Expansion Training: An Efficient Optimization Framework**

Michal Derezinski, Dhruv Mahajan, Sathiya Keerthi, S. V. N. Vishwanathan,
Markus Weimer

Poster 51: **Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems**

Sai Praneeth Reddy Karimireddy,
Sebastian Stich, Martin Jaggi

Poster 52: **Frank-Wolfe Splitting via Augmented Lagrangian Method**

Gauthier Gidel,
Fabian Pedregosa, Simon Lacoste-Julien,

Poster 53: **Structured Optimal Transport**

David Alvarez Melis, Tommi Jaakkola,
Stefanie Jegelka

Poster 54: **Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods**

Robert Gower, Nicolas Le Roux,
Francis Bach