[Nmlrg] a few references I mentioned yesterday

David Meyer <dmm@1-4-5.net> Tue, 19 July 2016 07:20 UTC

Return-Path: <dmm@1-4-5.net>
X-Original-To: nmlrg@ietfa.amsl.com
Delivered-To: nmlrg@ietfa.amsl.com
Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 50B1A12D133 for <nmlrg@ietfa.amsl.com>; Tue, 19 Jul 2016 00:20:52 -0700 (PDT)
X-Virus-Scanned: amavisd-new at amsl.com
X-Spam-Flag: NO
X-Spam-Score: -2.599
X-Spam-Level:
X-Spam-Status: No, score=-2.599 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_LOW=-0.7] autolearn=ham autolearn_force=no
Authentication-Results: ietfa.amsl.com (amavisd-new); dkim=pass (2048-bit key) header.d=1-4-5-net.20150623.gappssmtp.com
Received: from mail.ietf.org ([4.31.198.44]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id Gr5gqs9pIPgY for <nmlrg@ietfa.amsl.com>; Tue, 19 Jul 2016 00:20:50 -0700 (PDT)
Received: from mail-it0-x235.google.com (mail-it0-x235.google.com [IPv6:2607:f8b0:4001:c0b::235]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 7D8E412D100 for <nmlrg@irtf.org>; Tue, 19 Jul 2016 00:20:50 -0700 (PDT)
Received: by mail-it0-x235.google.com with SMTP id u186so86134339ita.0 for <nmlrg@irtf.org>; Tue, 19 Jul 2016 00:20:50 -0700 (PDT)
DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1-4-5-net.20150623.gappssmtp.com; s=20150623; h=mime-version:from:date:message-id:subject:to; bh=VQtBMkM5ImXWgRDmXIrU6uxuDzWH4X6DyZ7cD0fAino=; b=pgqh5rECgv2ZKxi6yisR1t3HoatFMCZ9IQOFR7KS92HIqguKmkwFudzfIWU/DGiMPB cI8IP3yPdzuepC78uX+Ug0WPgtwjt112VF59brQN1e2mvEslPhHsjRzHiK+KfC28mhvo U183WknoVvTf3MZIOl2VvtTyrvWmskhlcI1zjRowoXf9BpxjsEXzs+/MHQzHzaHNPHCC T4dgSvHbz0H2k3k3pw/a/+vCCO/AIbg7r2VAjzh/xFXgb3ahaJkTfOpud5R4fjA2kjVg x2bGMYvgEazNVokRz6LxplfXQC1ODTrb8krDQ2hr6BeNcGhmJYaTWeecx2ve9nfNtR7K soKg==
X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20130820; h=x-gm-message-state:mime-version:from:date:message-id:subject:to; bh=VQtBMkM5ImXWgRDmXIrU6uxuDzWH4X6DyZ7cD0fAino=; b=FFCFiF++Cq2+X6hea4qwRob0llAB7TfB655jNFjfYwcfmsec0DRaACIeF7UhjGJrWW XgZgAtyKZcS1hahuPKYqoSQscgwhxy7apODwCHCp/ZReYJ/D49VGIGofTWTKY+4y8zGU 6Fh+F0s4F0fCClbwmghwQ35JPXk1979+VweUcPaPdqDErz3WaEDPMF7ArMuanYjzTKLR CUcu8FB/pz65QmjAMuqURfTb87+z3vWhm+i5IfXtPsqa4+eEf8loZfEvLw63Te2P9u/B FaCsYBZKxwnBYq18DFENab8R1nBa6XXhMtVZ1pG4xsTHs0XadSlKKfDSxAOhw1hM9OcL w4ag==
X-Gm-Message-State: ALyK8tJWdG+FjzOn/vo9PAzu4N4uMIEtWMvILbY5RZpfhYkr9I4Yy/K1HkbxMVuj9U48jlagn4OcTqfDY8XlYw==
X-Received: by 10.36.227.13 with SMTP id d13mr2387962ith.18.1468912849507; Tue, 19 Jul 2016 00:20:49 -0700 (PDT)
MIME-Version: 1.0
Received: by 10.64.227.203 with HTTP; Tue, 19 Jul 2016 00:20:48 -0700 (PDT)
X-Originating-IP: [31.133.143.218]
From: David Meyer <dmm@1-4-5.net>
Date: Tue, 19 Jul 2016 09:20:48 +0200
Message-ID: <CAHiKxWhXoa1WbqZFRqJ+fJiqQG64LtGT1g-EBBTpCy24OeTtOw@mail.gmail.com>
To: nmlrg@irtf.org
Content-Type: multipart/alternative; boundary="94eb2c111b8c9a0c220537f7eccc"
Archived-At: <https://mailarchive.ietf.org/arch/msg/nmlrg/3gvyUUbWuB5IxHGTPnPVojVSNzE>
Subject: [Nmlrg] a few references I mentioned yesterday
X-BeenThere: nmlrg@irtf.org
X-Mailman-Version: 2.1.17
Precedence: list
List-Id: Network Machine Learning Research Group <nmlrg.irtf.org>
List-Unsubscribe: <https://www.irtf.org/mailman/options/nmlrg>, <mailto:nmlrg-request@irtf.org?subject=unsubscribe>
List-Archive: <https://mailarchive.ietf.org/arch/browse/nmlrg/>
List-Post: <mailto:nmlrg@irtf.org>
List-Help: <mailto:nmlrg-request@irtf.org?subject=help>
List-Subscribe: <https://www.irtf.org/mailman/listinfo/nmlrg>, <mailto:nmlrg-request@irtf.org?subject=subscribe>
X-List-Received-Date: Tue, 19 Jul 2016 07:20:52 -0000

(i).   On adversarial images; The canonical reference is here:
http://arxiv.org/pdf/1312.6199v4.pdf. More recent work on Generative
Adversarial Nets (GANs) here:
https://papers.nips.cc/paper/5423-generative-adversarial-nets.pdf (GANs
have emerged as a new and promising technique for unsupervised training).

(ii).  On AlphaGo:
http://www.nature.com/nature/journal/v529/n7587/pdf/nature16961.pdf and
http://www.nature.com/news/google-ai-algorithm-masters-ancient-game-of-go-1.19234.
If you are interested in more on reinforcement learning see Sutton's book
(Reinforcement Learning: An Introduction; you can find it online from
several sources).

(iii).  On LDA and other statistical clustering techniques for
high-cardinality categorical data:
http://www.1-4-5.net/~dmm/ml/lda_intro.pdf (see also
http://www.1-4-5.net/~dmm/ml/)

Thx,

--dmm