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---
layout: default
title: Home
id: home
---
<section class="events schedule half">
<h1>
Events
<span><a href="/sponsor/">Sponsored</a> by Facebook, Microsoft, Ness, Qualcomm, GreenGoose, Boeing, &amp; Stanford Computer Forum.</span>
</h1>
<h2 data-year="2012">
Fall
</h2>
</section>
<section class="techtalks schedule half">
<h1>
Tech Talks
<span>Sponsored by Yahoo. <strong>Every Friday @ 6 PM in Gates 104.</strong><br>
If you want to give a tech talk, <a href="/techtalks">read this</a>.
</span>
</h1>
<h2 data-year="2012">
Fall
</h2>
<time>September 28, 2012</time>
<div>
<span>Charlie Cheever</span>
<span>Co-founder, Quora</span>
<p>TBD</p>
</div>
<time>October 5, 2012</time>
<div>
<span>Tony Zhang</span>
<span>Hulu Software Engineer – CS '09</span>
<p>Given a discrete probability distribution, one can sample from it quickly using standard algorithms such as the alias method (Walker 1977). However, these algorithms assume the distribution does not change between samples, that is, the sampling is done with replacement. We present an efficient algorithm for sampling from a discrete probability distribution without replacement and its application at Hulu.</p>
</div>
<div>
<span>Karthik Viswanathan</span>
<span>Undergraduate - CS '15</span>
<p>Development efficiency is vital to save time and iterate quickly. In an effort to improve front-end efficiency, <a href="https://github.com/karthikv/nodefront">Nodefront</a>, a Node.js-powered utility, bundles a static site compiler, live development server, library fetcher, and build utility into one, simple command-line tool. Best of all, it's free and open source. Join Karthik for an introduction to Nodefront and how it can help your workflow.</p>
</div>
</section>