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155. Archiving scientific data

Author

Buneman, Peter, Khanna, Sanjeev, Tajima, Keishi, and Tan, Wang-Chiew

Subjects
Database, CD-ROM database, CD-ROM catalog, Databases -- Research
Abstract

Archiving is important for scientific data, where it is necessary to record all past versions of a database in order to verify findings based upon a specific version. Much scientific data is held in a hierachical format and has a key structure that provides a canonical identification for each element of the hierarchy. In this article, we exploit these properties to develop an archiving technique that is both efficient in its use of space and preserves the continuity of elements through versions of the database, something that is not provided by traditional minimum-edit-distance diff approaches. The approach also uses timestamps. All versions of the data are merged into one hierarchy where an element appearing in multiple versions is stored only once along with a timestamp. By identifying the semantic continuity of elements and merging them into one data structure, our technique is capable of providing meaningful change descriptions, the archive allows us to easily answer certain temporal queries such as retrieval of any specific version from the archive and finding the history of an element. This is in contrast with approaches that store a sequence of deltas where such operations may require undoing a large number of changes or significant reasoning with the deltas.

Published
2004

170. Quality of life after pharmacomechanical catheter-directed thrombolysis for proximal deep venous thrombosis

Author

Kahn, Susan R., primary, Julian, Jim A., additional, Kearon, Clive, additional, Gu, Chu-Shu, additional, Cohen, David J., additional, Magnuson, Elizabeth A., additional, Comerota, Anthony J., additional, Goldhaber, Samuel Z., additional, Jaff, Michael R., additional, Razavi, Mahmood K., additional, Kindzelski, Andrei L., additional, Schneider, Joseph R., additional, Kim, Paul, additional, Chaer, Rabih, additional, Sista, Akhilesh K., additional, McLafferty, Robert B., additional, Kaufman, John A., additional, Wible, Brandt C., additional, Blinder, Morey, additional, Vedantham, Suresh, additional, Sichlau, Michael, additional, Vlahos, Athanasios, additional, Smith, Steven, additional, Thalheimer, Quinn, additional, Singh, Nisha, additional, Harting, Rekha, additional, Gocke, John, additional, Guth, Scott, additional, Shah, Neel, additional, Brady, Paul, additional, Schatz, Marvin, additional, Horrow, Mindy, additional, Markazi, Peyman, additional, Forouzan, Leli, additional, Matalon, Terence A.S., additional, Hertzog, David, additional, Goday, Swapna, additional, Kennedy, Margaret, additional, Kaplan, Robert, additional, Campbell, Thomas, additional, Hartman, Jamie, additional, Nahum, Elmer, additional, Venkat, Arvind, additional, Krishnamurthy, Venkataramu, additional, Rectenwald, John, additional, Henke, Peter, additional, Eliason, Jonathan, additional, Willatt, Jonathon, additional, Escobar, Guillermo, additional, Samuels, Shaun, additional, Katzen, Barry, additional, Benenati, James, additional, Powell, Alex, additional, Pena, Constantino, additional, Wallach, Howard, additional, Gandhi, Ripal, additional, Schneider, Joseph, additional, Kim, Stanley, additional, Hashemi, Farrah, additional, Boyle, Joseph, additional, Patel, Nilesh, additional, Verta, Michael, additional, Leung, Daniel, additional, Garcia, Marc, additional, Blatt, Phillip, additional, Khatri, Jamil, additional, Epstein, Dave, additional, Ryan, Randall, additional, Sweeny, Tom, additional, Stillabower, Michael, additional, Kimbiris, George, additional, Raman, Tuhina, additional, Sierzenski, Paul, additional, Getto, Lelia, additional, Dignazio, Michael, additional, Horvath, Mark, additional, Gornik, Heather, additional, Bartholomew, John, additional, Shishehbor, Mehdi, additional, Peacock, Frank, additional, Joseph, Douglas, additional, Kim, Soo Hyum, additional, Mahlay, Natalia Fendrikova, additional, Clair, Daniel, additional, Lyden, Sean, additional, Kapoor, Baljendra, additional, McLennon, Gordon, additional, Pierce, Gregory, additional, Newman, James, additional, Spain, James, additional, Gill, Amanjiit, additional, Hamilton, Aaron, additional, Rizzo, Anthony, additional, Park, Woosup, additional, Dietzek, Alan, additional, Galin, Ira, additional, Plummer, Dahlia, additional, Hsu, Richard, additional, Broderick, Patrick, additional, Keller, Andrew, additional, Sayeed, Sameer, additional, Slater, Dennis, additional, Lustberg, Herb, additional, Akus, Jan, additional, Sidman, Robert, additional, Dhami, Mandeep, additional, Kohanski, Phillip, additional, Bulgaru, Anca, additional, Dulala, Renuka, additional, Burch, James, additional, Kapur, Dinesh, additional, Yang, Jie, additional, Ranson, Mark, additional, Wladis, Alan, additional, Varnagy, David, additional, Mekhail, Tarek, additional, Winter, Robert, additional, Perez-Izquierdo, Manuel, additional, Motew, Stephen, additional, Royd-Kranis, Robin, additional, Workman, Raymond, additional, Kribbs, Scott, additional, Hogsette, Gerald, additional, Moore, Phillip, additional, Thomason, Bradley, additional, Means, William, additional, Bonsall, Richard, additional, Stewart, John, additional, Golwya, Daniel, additional, Azene, Ezana, additional, Bottner, Wayne, additional, Bishop, William, additional, Clayton, Dave, additional, Gundersen, Lincoln, additional, Riherd, Jody, additional, Shakhnovich, Irina, additional, Ziegelbein, Kurt, additional, Chang, Thomas, additional, Sharma, Karun, additional, Allison, Sandra, additional, Banovac, Fil, additional, Cohen, Emil, additional, Furlong, Brendan, additional, Kessler, Craig, additional, McCullough, Mike, additional, Spies, Jim, additional, Lin, Judith, additional, Kaatz, Scott, additional, Getzen, Todd, additional, Miller, Joseph, additional, Schwartz, Scott, additional, Kabbani, Loay, additional, McVinnie, David, additional, Rundback, John, additional, Manno, Joseph, additional, Schwab, Richard, additional, Cole, Randolph, additional, Herman, Kevin, additional, Singh, David, additional, Barkama, Ravit, additional, Patel, Amish, additional, Comerota, Anthony, additional, Pigott, John, additional, Seiwert, Andrew, additional, Whalen, Ralph, additional, Russell, Todd, additional, Assi, Zakaria, additional, Kazanjian, Sahira, additional, Yobbagy, Jonathan, additional, Kaminski, Brian, additional, Kaufman, Allan, additional, Begeman, Garett, additional, DiSalle, Robert, additional, Thakur, Subash, additional, Jacquet, Marc, additional, Dykes, Thomas, additional, Gerding, Joseph, additional, Baker, Christopher, additional, Debiasto, Mark, additional, Mittleider, Derek, additional, Higgins, George, additional, Amberson, Steven, additional, Pezzuti, Roger, additional, Gallagher, Thomas, additional, Schainfeld, Robert, additional, Wicky, Stephan, additional, Kalva, Sanjeeva, additional, Walker, Gregory, additional, Salazar, Gloria, additional, Pomerantz, Benjamin, additional, Patel, Virenda, additional, Kabrhel, Christopher, additional, Iqbal, Shams, additional, Gangull, Suvranu, additional, Oklu, Rahmi, additional, Brannan, Scott, additional, Misra, Sanjay, additional, Bjarnason, Haraldur, additional, Ashrani, Aneel, additional, Caccavale, Michael, additional, Fleming, Chad, additional, Friese, Jeremy, additional, Heit, John, additional, Kalra, Manju, additional, Macedo, Thanila, additional, McBane, Robert, additional, McKusick, Michael, additional, Stockland, Andrew, additional, Woodrum, David, additional, Wysokinski, Waldemar, additional, Verma, Adarsh, additional, Davis, Andrew, additional, Chung, Jerry, additional, Nicker, David, additional, Anderson, Brian, additional, Stein, Robert, additional, Weiss, Michael, additional, Patel, Parag, additional, Rilling, William, additional, Tutton, Sean, additional, Hieb, Robert, additional, Hohenwalter, Eric, additional, Colella, M. Riccardo, additional, Gosset, James, additional, White, Sarah, additional, Lewis, Brian, additional, Brown, Kellie, additional, Rossi, Peter, additional, Seabrook, Gary, additional, Guimaraes, Marcelo, additional, Selby, J. Bayne, additional, McGary, William, additional, Hannegan, Christopher, additional, Robison, Jacob, additional, Brothers, Thomas, additional, Elliott, Bruce, additional, Garg, Nitin, additional, Anderson, M. Bret, additional, Uflacker, Renan, additional, Schonholz, Claudio, additional, Raney, Laurence, additional, Greenberg, Charles, additional, Kaufman, John, additional, Keller, Frederick, additional, Kolbeck, Kenneth, additional, Landry, Gregory, additional, Mitchell, Erica, additional, Barton, Robert, additional, DeLoughery, Thomas, additional, Kalbfleisch, Norman, additional, Minjarez, Renee, additional, Lakin, Paul, additional, Liem, Timothy, additional, Moneta, Gregory, additional, Farsad, Khashayar, additional, Fleischman, Ross, additional, French, Loren, additional, Marques, Vasco, additional, Al−Hassani, Yasir, additional, Sawar, Asad, additional, Taylor, Frank, additional, Patel, Rajul, additional, Malhotra, Rahul, additional, Hashemi, Farah, additional, Padnick, Marvin, additional, Gurley, Melissa, additional, Cucher, Fred, additional, Sterrenberg, Ronald, additional, Deepthi, G. Reshmaal, additional, Cumaranatunge, Gomes, additional, Bhatla, Sumit, additional, Jacobs, Darick, additional, Dolen, Eric, additional, Gamboa, Pablo, additional, Dean, L. Mark, additional, Davis, Thomas, additional, Lippert, John, additional, Khanna, Sanjeev, additional, Schirf, Brian, additional, Silber, Jeffrey, additional, Wood, Donald, additional, McGraw, J. Kevin, additional, LaPerna, Lucy, additional, Willette, Paul, additional, Murphy, Timothy, additional, Cerezo, Joselyn, additional, Dhangana, Rajoo, additional, Ahn, Sun Ho, additional, Dubel, Gregory, additional, Haas, Richard, additional, Jay, Bryan, additional, Prince, Ethan, additional, Soares, Gregory, additional, Klinger, James, additional, Lambiase, Robert, additional, Jay, Gregory, additional, Tubbs, Robert, additional, Beland, Michael, additional, Hampson, Chris, additional, O'Hara, Ryan, additional, Thompson, Chad, additional, Frodsham, Aaron, additional, Gardiner, Fenwick, additional, Jaffan, Abdel, additional, Keating, Lawrence, additional, Zafar, Abdul, additional, Alicic, Radica, additional, Raabe, Rodney, additional, Brower, Jayson, additional, McClellan, David, additional, Pellow, Thomas, additional, Zylak, Christopher, additional, Davis, Joseph, additional, Reilly, M. Kathleen, additional, Symington, Kenneth, additional, Seibold, Camerson, additional, Nachreiner, Ryan, additional, Murray, Daniel, additional, Murray, Stephen, additional, Saha, Sandeep, additional, Luna, Gregory, additional, Hodgson, Kim, additional, McLafferty, Robert, additional, Hood, Douglas, additional, Moore, Colleen, additional, Griffen, David, additional, Hurst, Darren, additional, Lubbers, David, additional, Kim, Daniel, additional, Warren, Brent, additional, Engel, Jeremy, additional, Suresh, D.P., additional, VanderWoude, Eric, additional, Razdan, Rahul, additional, Hutchins, Mark, additional, Rounsborg, Terry, additional, Midathada, Madhu, additional, Moravec, Daniel, additional, Tilford, Joni, additional, Beckman, Joni, additional, Razavi, Mahmood, additional, Openshaw, Kurt, additional, Flanigan, D. Preston, additional, Loh, Christopher, additional, Dorne, Howard, additional, Chan, Michael, additional, Thomas, Jamie, additional, Psaila, Justin, additional, Ringold, Michael, additional, Fisher, Jay, additional, Lipcomb, Any, additional, Oskin, Timothy, additional, Wible, Brandt, additional, Coleman, Brendan, additional, Elliott, David, additional, Gaddis, Gary, additional, Cochran, C. Doug, additional, Natarajan, Kannan, additional, Bick, Stewart, additional, Cooke, Jeffrey, additional, Hedderman, Ann, additional, Greist, Anne, additional, Miller, Lorrie, additional, Martinez, Brandon, additional, Flanders, Vincent, additional, Underhill, Mark, additional, Hofmann, Lawrence, additional, Sze, Daniel, additional, Kuo, William, additional, Louie, John, additional, Hwang, Gloria, additional, Hovsepian, David, additional, Kothary, Nishita, additional, Berube, Caroline, additional, Schreiber, Donald, additional, Jeffrey, Brooke, additional, Schor, Jonathan, additional, Deitch, Jonathan, additional, Singh, Kuldeep, additional, Hahn, Barry, additional, Ardolic, Brahim, additional, Gupta, Shilip, additional, Bashir, Riyaz, additional, Rao, Angara Koneti, additional, Garg, Manish, additional, Patil, Pravin, additional, Zack, Chad, additional, Cohen, Gary, additional, Schmieder, Frank, additional, Lakhter, Valdimir, additional, Sacks, David, additional, Guay, Robert, additional, Scott, Mark, additional, Cunningham, Karekin, additional, Sigal, Adam, additional, Cescon, Terrence, additional, Leasure, Nick, additional, Dhurairaj, Thiruvenkatasamy, additional, Muck, Patrick, additional, Knochel, Kurt, additional, Lohr, Joann, additional, Barreau, Jose, additional, Recht, Matthew, additional, Bhaskaran, Jayapandia, additional, Brahmamdam, Ranga, additional, Draper, David, additional, Mehta, Apurva, additional, Maher, James, additional, Sharafuddin, Melhem, additional, Lentz, Steven, additional, Nugent, Andrew, additional, Sharp, William, additional, Kresowik, Timothy, additional, Nicholson, Rachel, additional, Sun, Shiliang, additional, Youness, Fadi, additional, Pascarella, Luigi, additional, Ray, Charles, additional, Knuttinen, Martha-Gracia, additional, Bui, James, additional, Gaba, Ron, additional, Dobiesz, Valerie, additional, Shamim, Ejaz, additional, Nimmagadda, Sangeetha, additional, Peace, David, additional, Zain, Aarti, additional, Palumto, Alison, additional, Haskal, Ziv, additional, Hirshon, Jon Mark, additional, Richard, Howard, additional, Verceles, Avelino, additional, Wong-You-Chong, Jade, additional, Othee, Bertrand, additional, Patel, Rahul, additional, Iliescu, Bogdan, additional, Williams, David, additional, Gemmete, Joseph, additional, Cwikiel, Wojciech, additional, Cho, Kyung, additional, Schields, James, additional, Vellody, Ranjith, additional, Novelli, Paula, additional, Dasika, Narasimham, additional, Wakefield, Thomas, additional, Desmond, Jeffrey, additional, Froehlich, James, additional, Khaja, Minhajuddin, additional, Hunter, David, additional, Golzarian, Jafar, additional, Cressman, Erik, additional, Dotta, Yvonne, additional, Schmiechen, Nate, additional, Marek, John, additional, Garcia, David, additional, Tawil, Isaac, additional, Langsfeld, Mark, additional, Moll, Stephan, additional, Mauro, Matthew, additional, Stavas, Joseph, additional, Burke, Charles, additional, Dixon, Robert, additional, Yu, Hyeon, additional, Keagy, Blair, additional, Kim, Kyuny, additional, Kasthuri, Raj, additional, Key, Nigel, additional, Makaroun, Michael, additional, Rhee, Robert, additional, Cho, Jae−Sung, additional, Baril, Donald, additional, Marone, Luke, additional, Hseih, Margaret, additional, Feterik, Kristian, additional, Smith, Roy, additional, Jeyabalan, Geetha, additional, Rogers, Jennifer, additional, Vinik, Russel, additional, Kinikini, Dan, additional, Kraiss, Larry, additional, Mueller, Michelle, additional, Pendleton, Robert, additional, Rondina, Matthew, additional, Sarfati, Mark, additional, Wanner, Nathan, additional, Johnson, Stacy, additional, Hopkins, Christy, additional, Ihnat, Daniel, additional, Angle, John, additional, Matsumoto, Alan, additional, Harthun, Nancy, additional, Turba, Ulku, additional, Saad, Wael, additional, Uthlaut, Brian, additional, Nannapaneni, Srikant, additional, Ling, David, additional, Sabri, Saher, additional, Kern, John, additional, Macik, B. Gail, additional, Hoke, George, additional, Park, Auh Wahn, additional, Stone, James, additional, Sneed, Benjamin, additional, Syverud, Scott, additional, Davidson, Kelly, additional, Sharma, Aditya, additional, Wilkins, Luke, additional, Black, Carl, additional, Asay, Mark, additional, Hatch, Daniel, additional, Smilanich, Robert, additional, Patten, Craig, additional, Brown, S. Douglas, additional, Nielsen, Ryan, additional, Alward, William, additional, Collins, John, additional, Nokes, Matthew, additional, Geary, Randolph, additional, Edwards, Matthew, additional, Godshall, Christopher, additional, Levy, Pavel, additional, Winokur, Ronald, additional, Sista, Akhilesh, additional, Madoff, David, additional, Lee, Kyungmouk, additional, Pua, Bradley, additional, DeSancho, Maria, additional, Milizia, Raffaele, additional, Gao, Jing, additional, McLean, Gordon, additional, Khalid, Sanualah, additional, Lewis, Larry, additional, Saad, Nael, additional, Thoelke, Mark, additional, Pallow, Robert, additional, Klein, Seth, additional, Sicard, Gregorio, additional, Gornik, Heather L., additional, Julian, Jim, additional, Kahn, Susan R., additional, Kee, Stephen, additional, Lewis, Lawrence, additional, Magnuson, Elizabeth, additional, and Murphy, Timothy P., additional

Published
2020
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182. Sensorimotor Encoding In Prefrontal Cortex

Author

Khanna, Sanjeev and Khanna, Sanjeev

Abstract

When processing the vast visual world in front of us, eye movements allow us to focus on specific relevant stimuli. To gather information about a stimulus, the brain must determine its location and plan an eye movement to that location. It is not fully understood how populations of neurons store the incoming visual input in a memory signal and then retrieve it to produce a fast and accurate motor output. We sought answers to this question by recording the activity of populations of neurons in cortical regions thought to be involved in the maintenance of working memory and the generation of eye movements. First, we analyzed how populations of neurons coordinated their activity during the period after a visual stimulus was presented, but before an eye movement was made. Specifically, we were interested in identifying the optimal activity profiles for generating a fast eye movement. We recorded from groups of neurons in the frontal eye fields (FEF), an area known to be important for saccade generation. We found neurons change their activity at both the individual level and by covarying their activity with other neurons to generate fast eye movements. We then recorded from neurons in prefrontal cortex (PFC) to determine how visual and motor signals are encoded at the single neuron and population level. For single neurons, we observed rich dynamics, including neurons that encoded the entire visual field, and neurons that shifted their tuning between visual and motor epochs. At the population level, these shifts in tuning created a dynamic population code. These single neuron properties were less likely to be observed in FEF, which resulted in FEF having a more stable population code when compared to PFC. In summary, the visual and motor representations associated with processing a stimulus and preparing an eye movement manifest in the activity of single neurons and populations, and their dynamics over time. These results lead to a richer view of working memory and eye mo

Published
2019

183. A Simple Sublinear-Time Algorithm for Counting Arbitrary Subgraphs via Edge Sampling

Author

Sepehr Assadi and Michael Kapralov and Sanjeev Khanna, Assadi, Sepehr, Kapralov, Michael, Khanna, Sanjeev, Sepehr Assadi and Michael Kapralov and Sanjeev Khanna, Assadi, Sepehr, Kapralov, Michael, and Khanna, Sanjeev

Abstract

In the subgraph counting problem, we are given a (large) input graph G(V, E) and a (small) target graph H (e.g., a triangle); the goal is to estimate the number of occurrences of H in G. Our focus here is on designing sublinear-time algorithms for approximately computing number of occurrences of H in G in the setting where the algorithm is given query access to G. This problem has been studied in several recent papers which primarily focused on specific families of graphs H such as triangles, cliques, and stars. However, not much is known about approximate counting of arbitrary graphs H in the literature. This is in sharp contrast to the closely related subgraph enumeration problem that has received significant attention in the database community as the database join problem. The AGM bound shows that the maximum number of occurrences of any arbitrary subgraph H in a graph G with m edges is O(m^{rho(H)}), where rho(H) is the fractional edge-cover of H, and enumeration algorithms with matching runtime are known for any H. We bridge this gap between subgraph counting and subgraph enumeration by designing a simple sublinear-time algorithm that can estimate the number of occurrences of any arbitrary graph H in G, denoted by #H, to within a (1 +/- epsilon)-approximation with high probability in O(m^{rho(H)}/#H) * poly(log(n),1/epsilon) time. Our algorithm is allowed the standard set of queries for general graphs, namely degree queries, pair queries and neighbor queries, plus an additional edge-sample query that returns an edge chosen uniformly at random. The performance of our algorithm matches those of Eden et al. [FOCS 2015, STOC 2018] for counting triangles and cliques and extend them to all choices of subgraph H under the additional assumption of edge-sample queries.

Published
2019
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185. Effect of fiber reinforcement on dynamic crack growth in brittle matrix composites

Author

Shukla, Arun and Khanna, Sanjeev K.

Subjects
Fibrous composites -- Research, Science and technology
Abstract

The dynamic fracture behavior of fiber reinforced polyestercomposites is investigated. Experiments are conducted wherein the dynamic physical properties of several polyester specimens are studied through photoelastic techniques. The crack velocity is then determined by analyzing thephotographs of the structures isochromatic fringe patterns. Results show that the fiber reinforcment helps in the reduction of the crack velocity and dynamicstress intensity factor.

Published
1993

189. TIGHT BOUNDS FOR SINGLE-PASS STREAMING COMPLEXITY OF THE SET COVER PROBLEM.

Author

ASSADI, SEPEHR, KHANNA, SANJEEV, and YANG LI

Subjects
*DATABASES, *APPROXIMATION algorithms, *OPEN-ended questions, *CASE goods
Abstract

We resolve the space complexity of single-pass streaming algorithms for approximating the classic set cover problem. For finding an α-approximate set cover (for any α = o(√n/log n)) using a single-pass streaming algorithm, we show that Θ(mn/α) space is both sufficient and necessary (up to an O(log n) factor); here m denotes the number of sets and n denotes the size of the universe. This provides a strong negative answer to the open question posed by Har-Peled et al. [Towards tight bounds for the streaming set cover problem, in Proceedings of the 35th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS '16), pp. 371-383] regarding the possibility of having a single-pass algorithm with a small approximation factor that uses sublinear space. We further study the problem of estimating the size of a minimum set cover (as opposed to finding the actual sets) and establish that an additional factor of α savings in the space is achievable in this case and is the best possible. In other words, we show that Θ(mn/α²) space is both sufficient and necessary (up to logarithmic factors) for estimating the size of a minimum set cover to within a factor of α. Our algorithm, in fact, works for the more general problem of estimating the optimal value of a covering integer program. On the other hand, our lower bound holds even for set cover instances, where the sets are presented in a random order. [ABSTRACT FROM AUTHOR]

Published
2021
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190. Sublinear Algorithms for $(��+ 1)$ Vertex Coloring

Author

Assadi, Sepehr, Chen, Yu, and Khanna, Sanjeev

Subjects
FOS: Computer and information sciences, Data Structures and Algorithms (cs.DS), MathematicsofComputing_DISCRETEMATHEMATICS
Abstract

Any graph with maximum degree $��$ admits a proper vertex coloring with $��+ 1$ colors that can be found via a simple sequential greedy algorithm in linear time and space. But can one find such a coloring via a sublinear algorithm? We answer this fundamental question in the affirmative for several canonical classes of sublinear algorithms including graph streaming, sublinear time, and massively parallel computation (MPC) algorithms. In particular, we design: * A single-pass semi-streaming algorithm in dynamic streams using $\tilde{O}(n)$ space. The only known semi-streaming algorithm prior to our work was a folklore O(log n)-pass algorithm obtained by simulating classical distributed algorithms in the streaming model. * A sublinear-time algorithm in the standard query model that allows neighbor queries and pair queries using $\tilde{O}(n\sqrt{n})$ time. We further show that any algorithm that outputs a valid coloring with sufficiently large constant probability requires $��(n\sqrt{n})$ time. No non-trivial sublinear time algorithms were known prior to our work. * A parallel algorithm in the massively parallel computation (MPC) model using $\tilde{O}(n)$ memory per machine and $O(1)$ MPC rounds. Our number of rounds significantly improves upon the recent $O(\log\log��\cdot\log^*{(n)})$-round algorithm of Parter [ICALP 2018]. At the core of our results is a remarkably simple meta-algorithm for the $(��+1)$ coloring problem: Sample $O(\log{n})$ colors for each vertex from the $��+1$ colors; find a proper coloring of the graph using only the sampled colors. We prove that the sampled set of colors with high probability contains a proper coloring of the input graph. The sublinear algorithms are then obtained by designing efficient algorithms for finding a proper coloring of the graph from the sampled colors in the corresponding models.

Published
2018
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