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---
title: Conference Schedule
layout: default
---
<h1>AISTATS*2012 Conference Schedule </h1>
<h3>Thursday 19 April </h3>
<table>
<tr>
<td width="20%" ><a name="registration1"></a>16:00 - 21:00</td>
<td width="90%">Registration
</td>
</tr>
</table>
<h3>Friday 20 April (AISTATS/MLSS Joint Tutorial Day) </h3>
<table>
<tr>
<td width="20%" ><a name="registration1"></a>07:45 - 09:00</td>
<td width="90%">Breakfast and Registration
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td>
<td width="90%"><b>
<a href="{{ site.baseurl }}/tutorials.html">Tutorials</a> Jointly with MLSS
</b></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="130"></a>09:00 - 11:00</td>
<td width="90%"> Nonparametric Bayesian Modelling
<br>
<i><em>Zoubin Ghahramani</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="294"></a>11:30 - 13:30</td>
<td width="90%">Probabilistic decision-making, data analysis, and discovery in astronomy<br>
<i><em>David W. Hogg </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="lunch1"></a>13:30 - 16:30</td>
<td width="90%">Lunch
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="poster1"></a>16:30 - 19:30</td>
<td width="90%">Poster Session for MLSS Students
</td>
</tr>
</table>
<h3>Saturday 21 April </h3>
<table>
<tr>
<td width="20%" ><a name="breakfast1"></a>07:45 - 08:45</td>
<td width="90%">Breakfast
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="invited1"></a>08:45 - 09:00</td>
<td width="90%">Welcome
<br><i>AISTATS Organizers</i>
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Invited Talk</b> (Chair: Mark Girolami)
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="invited3"></a>09:00 - 10:00</td>
<td width="90%">Detection of correlations in high dimension <br>
<i>Gábor Lugosi</i> </td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td>
<td width="90%"><b>Kernel Methods
</b> (Chair: Philipp Hennig)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="130"></a>10:00 - 10:25</td>
<td width="90%">Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness
<br>
<i><em>Taiji Suzuki and Masashi Sugiyama</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="294"></a>10:25 - 10:50</td>
<td width="90%">Data dependent kernels in nearly-linear time<br>
<i><em>Guy Lever, Tom Diethe and John Shawe-Taylor </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="coffee1"></a>11:00 - 13:00</td>
<td width="90%">Coffee Break and <a href="{{ site.baseurl }}/poster_session.html#Poster1">Poster Session I</a><br />
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="lunch1"></a>13:00 - 17:00</td>
<td width="90%">Lunch
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td>
<td width="90%"><b>Bayesian Inference
</b> (Chair: Zoubin Ghahramani)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="257"></a>17:00 - 17:25</td>
<td width="90%">Factorized Asymptotic Bayesian Inference for Mixture Modeling
<br>
<i><em>Ryohei Fujimaki and Satoshi Morinaga </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="242"></a>17:25 - 17:50</td>
<td width="90%">Adaptive MCMC with Bayesian Optimization<br>
<i><em>Nimalan Mahendran, Ziyu Wang, Firas Hamze and Nando de Freitas </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="157"></a>17:50 - 18:15</td>
<td width="90%">Evaluation of marginal likelihoods via the density of states<br>
<i><em>Michael Habeck</em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="tea1"></a>18:15 - 18:45</td>
<td width="90%">Tea Break
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Structure Learning and Sparsity</b> (Chair: Jennifer Dy) </td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="100"></a>18:45 - 19:10</td>
<td width="90%">Lightning-speed Structure Learning of Nonlinear Continuous Networks<br>
<i><em>Gal Elidan</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="167"></a>19:10 - 19:35</td>
<td width="90%">High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods<br />
<i><em>Christopher Johnson, Ali Jalali, and Pradeep Ravikumar </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="318"></a>19:35 - 20:00</td>
<td width="90%">Learning Fourier Sparse Set Functions<br>
<i><em>Peter Stobbe and Andreas Krause </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="banquet1"></a>20:00 - 22:00</td>
<td width="90%">Conference Banquet
</td>
</tr>
</table>
<h3>Sunday 22 April </h3>
<table>
<tr>
<td width="20%" ><a name="breakfast2"></a>07:45 - 09:00</td>
<td width="90%">Breakfast
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Invited Talk</b> (Chair: Neil Lawrence)
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="invited1"></a>09:00 - 10:00</td>
<td width="90%">Patterns, Predictions and Personalised Medicine<br />
<i>Sir Gordon Duff </i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Scientific Computing & Speed Ups</b> (Chair: Felix Agakov)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="296"></a>10:00 - 10:25</td>
<td width="90%">A Bayesian Analysis of the Radioactive Releases of Fukushima<br />
<i><em>Ryota Tomioka and Morten Mørup </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="255"></a>10:25 - 10:50</td>
<td width="90%">Using More Data to Speed-up Training Time <br />
<i><em>Shai Shalev-Shwartz, Ohad Shamir and Eran Tromer </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="coffee2"></a>11:00 - 13:00</td>
<td width="90%">Coffee Break and <a href="{{ site.baseurl }}/poster_session.html#Poster2">Poster Session II</a><br />
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="lunch2"></a>13:00 - 17:00</td>
<td width="90%">Lunch
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Clustering & Learning Theory</b> (Chair: Shai Ben-David)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="117"></a>17:00 - 17:25</td>
<td width="90%">Online Clustering with Experts<br>
<i><em>Anna Choromanska and Claire Monteleoni</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="309"></a>17:25 - 17:50</td>
<td width="90%">Maximum Margin Temporal Clustering<br>
<i><em>Minh Hoai and Fernando De la Torre </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="274"></a>17:50 - 18:15</td>
<td width="90%">Minimax rates for homology inference<br>
<i><em>Sivaraman Balakrishnan, Alesandro Rinaldo, Don Sheehy, Aarti Singh and Larry Wasserman </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="tea2"></a>18:15 - 18:45</td>
<td width="90%">Tea Break
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Feature Extraction and Bandits</b> (Chair: Amos Storkey)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="233"></a>18:45 - 19:10</td>
<td width="90%">Online Incremental Feature Learning with Denoising Autoencoders<br>
<i><em>Guanyu Zhou, Kihyuk Sohn and Honglak Lee</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="149"></a>19:10 - 19:35</td>
<td width="90%">Classifier Cascade for Minimizing Feature Evaluation Cost<br>
<i><em>Minmin Chen, Zhixiang Xu, Kilian Weinberger, Olivier Chapelle and Dor Kedem</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="113"></a>19:35 - 20:00</td>
<td width="90%">Online-to-Confidence-Set Conversions and Application to Sparse Stochastic Bandits<br>
<i><em>Yasin Abbasi-Yadkori, David Pal and Csaba Szepesvari </em></i></td>
</tr>
</table>
<!-- <p>
<table>
<tr>
<td width="20%" ><a name="dinner2"></a>20:00 - 22:00</td>
<td width="90%">Dinner</td> -->
</tr>
</table>
<h3>Monday 23 April </h3>
<table>
<tr>
<td width="20%" ><a name="breakfast3"></a>07:45 - 09:00</td>
<td width="90%">Breakfast
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Invited Talk</b> (Chair: Bernhard Schölkopf)
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="invited2"></a>09:00 - 10:00</td>
<td width="90%">Alpha, Betti and the Megaparsec Universe: Topology of the Cosmic Web<br><i>Rien van de Weygaert
</i> </td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Sparse Analysis
</b> (Chair: Dirk Husmeier)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="66"></a>10:00 - 10:25</td>
<td width="90%">Minimax Rates of Estimation for Sparse PCA in High Dimensions<br>
<i><em>Vincent Vu and Jing Lei </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="134"></a>10:25 - 10:50</td>
<td width="90%">Structured Sparse Canonical Correlation Analysis<br>
<i><em>Xi Chen, Liu Han and Jaime Carbonell </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="coffee2"></a>11:00 - 13:00</td>
<td width="90%">Coffee Break and <a href="{{ site.baseurl }}/poster_session.html#Poster3">Poster Session III</a><br />
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="lunch3"></a>13:00 - 17:00</td>
<td width="90%">Lunch
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td>
<td width="90%"><b>Multitask, Multiparty and Multilabels</b> (Chair: Miguel Carreira-Perpinan)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="259"></a>17:00 - 17:25</td>
<td width="90%">Marginal Regression For Multitask Learning<br>
<i><em>Mladen Kolar and Han Liu </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="251"></a>17:25 - 17:50</td>
<td width="90%">A Differentially Private Stochastic Gradient Descent Algorithm for Multiparty Classification<br />
<i><em>Arun Rajkumar and Shivani Agarwal</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="241"></a>17:50 - 18:15</td>
<td width="90%">CorrLog: Correlated Logistic Models for Joint Prediction of Multiple Labels
<br>
<i><em>Wei Bian, Bo Xie and Dacheng Tao </em></i></td>
</tr>
</table>
<p>
<table>
<tr>
<td width="20%" ><a name="tea1"></a>18:15 - 18:45</td>
<td width="90%">Tea Break
</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ></td> <td width="90%"><b>Regression Modelling</b> (Chair: John Winn)</td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="151"></a>18:45 - 19:10</td>
<td width="90%">Hierarchical Latent Dictionaries for Models of Brain Activation<br>
<i><em>Alona Fyshe, Emily Fox, David Dunson and Tom Mitchell</em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="43"></a>19:10 - 19:35</td>
<td width="90%">Efficient Gaussian Process Inference for Short-Scale Spatio-Temporal Modeling<br />
<i><em>Jaakko Luttinen and Alexander Ilin </em></i></td>
</tr>
</table>
<table>
<tr>
<td width="20%" ><a name="225"></a>19:35 - 20:00</td>
<td width="90%">Regression for sets of polynomial equations
<br>
<i><em>Franz Király, Paul von Büenau, Jan Müller, Duncan Blythe, Frank Meinecke, and Klaus-Robert Müller</em></i></td>
</tr>
</table>