https://sublinear.info/index.php?title=Open_Problems:73&feed=atom&action=historyOpen Problems:73 - Revision history2024-03-29T07:01:52ZRevision history for this page on the wikiMediaWiki 1.31.10https://sublinear.info/index.php?title=Open_Problems:73&diff=958&oldid=prevKrzysztof Onak: Updating header2016-01-18T18:43:33Z<p>Updating header</p>
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<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">|title=Streaming online algorithms</del></div></td><td colspan="2"> </td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|source=baltimore16</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|source=baltimore16</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|who=Edo Liberty</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|who=Edo Liberty</div></td></tr>
</table>Krzysztof Onakhttps://sublinear.info/index.php?title=Open_Problems:73&diff=953&oldid=prevKrzysztof Onak: Krzysztof Onak moved page Waiting:73 to Open Problems:73 without leaving a redirect: Moving to main list of problems2016-01-18T18:40:07Z<p>Krzysztof Onak moved page <a href="/index.php?title=Waiting:73&action=edit&redlink=1" class="new" title="Waiting:73 (page does not exist)">Waiting:73</a> to <a href="/index.php?title=Open_Problems:73" title="Open Problems:73">Open Problems:73</a> without leaving a redirect: Moving to main list of problems</p>
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</td></tr></table>Krzysztof Onakhttps://sublinear.info/index.php?title=Open_Problems:73&diff=952&oldid=prevKrzysztof Onak: Krzysztof Onak moved page Waiting:Edo to Waiting:73 without leaving a redirect: Moving to main list of problems2016-01-18T18:39:35Z<p>Krzysztof Onak moved page <a href="/index.php?title=Waiting:Edo&action=edit&redlink=1" class="new" title="Waiting:Edo (page does not exist)">Waiting:Edo</a> to <a href="/index.php?title=Waiting:73&action=edit&redlink=1" class="new" title="Waiting:73 (page does not exist)">Waiting:73</a> without leaving a redirect: Moving to main list of problems</p>
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</td></tr></table>Krzysztof Onakhttps://sublinear.info/index.php?title=Open_Problems:73&diff=920&oldid=prevKrzysztof Onak: Small edits2016-01-12T21:54:43Z<p>Small edits</p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|who=Edo Liberty</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|who=Edo Liberty</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>A tad more open-ended than the usual open problems from this website, this one arises from the following observation. While streaming algorithms are often motivated by the constraints due to <del class="diffchange diffchange-inline">"</del>big data,<del class="diffchange diffchange-inline">" </del>in practice this data is not ''static'': however, most streaming algorithms use the structure and regularities encountered in the stream to compute solutions or results only available at the end of the streaming, in hindsight.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>A tad more open-ended than the usual open problems from this website, this one arises from the following observation. While streaming algorithms are often motivated by the constraints due to <ins class="diffchange diffchange-inline">&ldquo;</ins>big data,<ins class="diffchange diffchange-inline">&rdquo; </ins>in practice this data is not ''static'': however, most streaming algorithms use the structure and regularities encountered in the stream to compute solutions or results only available at the end of the streaming, in hindsight.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>In practice, however, one often needs to be ''online'' as well: that is, to maintain a <del class="diffchange diffchange-inline">"</del>good as of now<del class="diffchange diffchange-inline">" </del>solution as the stream goes, and to combine the usual memory constraints of the streaming setting with the objectives of the standard online analysis setting. (Note that, in contrast to the majority of the machine learning literature, one cannot in general make the assumption of stochasticity; the performance thus has to be compared in the adversarial setting, or an intermediate, better suited model has to be developed.)</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>In practice, however, one often needs to be ''online'' as well: that is, to maintain a <ins class="diffchange diffchange-inline">&ldquo;</ins>good as of now<ins class="diffchange diffchange-inline">&rdquo; </ins>solution as the stream goes, and to combine the usual memory constraints of the streaming setting with the objectives of the standard online analysis setting. (Note that, in contrast to the majority of the machine learning literature, one cannot in general make the assumption of stochasticity; the performance thus has to be compared in the adversarial setting, or an intermediate, better suited model has to be developed.)</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Question:''' <del class="diffchange diffchange-inline">which </del>model can capture this real-world need for a combination of streaming and online competitivity constraints, and what algorithms can then one obtain in this model?</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Question:''' <ins class="diffchange diffchange-inline">Which </ins>model can capture this real-world need for a combination of streaming and online competitivity constraints, and what algorithms can then one obtain in this model?</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Note:''' <del class="diffchange diffchange-inline">for </del>some work in this direction, one can consult {{cite|LibertySS-16}}.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Note:''' <ins class="diffchange diffchange-inline">For </ins>some work in this direction, one can consult {{cite|LibertySS-16}}.</div></td></tr>
</table>Krzysztof Onakhttps://sublinear.info/index.php?title=Open_Problems:73&diff=903&oldid=prevCcanonne at 02:03, 12 January 20162016-01-12T02:03:18Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 02:03, 12 January 2016</td>
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<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A tad more open-ended than the usual open problems from this website, this one arises from the following observation. While streaming algorithms are often motivated by the constraints due to "big data," in practice this data is not ''static'': however, most streaming algorithms use the structure and regularities encountered in the stream to compute solutions or results only available at the end of the streaming, in hindsight.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>A tad more open-ended than the usual open problems from this website, this one arises from the following observation. While streaming algorithms are often motivated by the constraints due to "big data," in practice this data is not ''static'': however, most streaming algorithms use the structure and regularities encountered in the stream to compute solutions or results only available at the end of the streaming, in hindsight.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>In practice, <del class="diffchange diffchange-inline">howver</del>, one often needs to be ''online'' as well: that is, to maintain a "good as of now" solution as the stream goes, and to combine the usual memory constraints of the streaming setting with the objectives of the standard online analysis setting. (Note that, in contrast to the majority of the machine learning literature, one cannot in general make the assumption of stochasticity; the performance thus has to be compared in the adversarial setting, or an intermediate, better suited model has to be developed.)</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>In practice, <ins class="diffchange diffchange-inline">however</ins>, one often needs to be ''online'' as well: that is, to maintain a "good as of now" solution as the stream goes, and to combine the usual memory constraints of the streaming setting with the objectives of the standard online analysis setting. (Note that, in contrast to the majority of the machine learning literature, one cannot in general make the assumption of stochasticity; the performance thus has to be compared in the adversarial setting, or an intermediate, better suited model has to be developed.)</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Question:''' which model can capture this real-world need for a combination of streaming and online competitivity constraints, and what algorithms can then one obtain in this model?</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Question:''' which model can capture this real-world need for a combination of streaming and online competitivity constraints, and what algorithms can then one obtain in this model?</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Note:''' for some work in this direction, one can consult {{cite|LibertySS-16}}.</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>'''Note:''' for some work in this direction, one can consult {{cite|LibertySS-16}}.</div></td></tr>
</table>Ccanonnehttps://sublinear.info/index.php?title=Open_Problems:73&diff=899&oldid=prevCcanonne at 01:58, 12 January 20162016-01-12T01:58:44Z<p></p>
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<td colspan="2" style="background-color: #fff; color: #222; text-align: center;">Revision as of 01:58, 12 January 2016</td>
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<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>|title=<del class="diffchange diffchange-inline">Title of the problem</del></div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>|title=<ins class="diffchange diffchange-inline">Streaming online algorithms</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|source=baltimore16</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|source=baltimore16</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|who=Edo Liberty</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>|who=Edo Liberty</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td><td class='diff-marker'> </td><td style="background-color: #f8f9fa; color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>}}</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del class="diffchange diffchange-inline">The </del>open <del class="diffchange diffchange-inline">problem will appear here</del>.</div></td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">A tad more </ins>open<ins class="diffchange diffchange-inline">-ended than the usual open problems from this website, this one arises from the following observation. While streaming algorithms are often motivated by the constraints due to "big data," in practice this data is not ''static'': however, most streaming algorithms use the structure and regularities encountered in the stream to compute solutions or results only available at the end of the streaming, in hindsight.</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">In practice, howver, one often needs to be ''online'' as well: that is, to maintain a "good as of now" solution as the stream goes, and to combine the usual memory constraints of the streaming setting with the objectives of the standard online analysis setting. (Note that, in contrast to the majority of the machine learning literature, one cannot in general make the assumption of stochasticity; the performance thus has to be compared in the adversarial setting, or an intermediate, better suited model has to be developed.)</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">'''Question:''' which model can capture this real-world need for a combination of streaming and online competitivity constraints, and what algorithms can then one obtain in this model?</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div> </div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color: #222; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins class="diffchange diffchange-inline">'''Note:''' for some work in this direction, one can consult {{cite|LibertySS-16}}</ins>.</div></td></tr>
</table>Ccanonnehttps://sublinear.info/index.php?title=Open_Problems:73&diff=876&oldid=prevKrzysztof Onak: Created page with "{{Header |title=Title of the problem |source=baltimore16 |who=Edo Liberty }} The open problem will appear here."2016-01-10T04:28:43Z<p>Created page with "{{Header |title=Title of the problem |source=baltimore16 |who=Edo Liberty }} The open problem will appear here."</p>
<p><b>New page</b></p><div>{{Header<br />
|title=Title of the problem<br />
|source=baltimore16<br />
|who=Edo Liberty<br />
}}<br />
The open problem will appear here.</div>Krzysztof Onak