Archive for United States of America
Deenaalee, na’al ts’ik’eh!
Posted in Mountains, pictures, Running, Travel with tags Alaska, Alaska Range, Athabaskan, baby Trump, Denali, Denali National Park, First Nations, Koyukon, National Park Service, the seven summits, United States of America, US politics, William McKinley on January 21, 2025 by xi'anthe world needs a US president who respects evidence [says Nature]
Posted in Kids, University life with tags @ScientistTrump, academic research, Congress, democracy, Democrats, Donald Trump, EPA, fake news, international collaboration, Kamala Harris, Nature, Second World War, The Inflation Reduction Act, United States of America, US elections 2024, US Science on November 4, 2024 by xi'an
[Reposted from Nature 634, 1017-1018 (2024)]
Next week, US voters will go to the polls to elect a new president, along with members of the House of Representatives and the Senate. This election will take place at a time of extreme uncertainty, both for the United States and for the world. The two candidates, Democrat Kamala Harris and Republican Donald Trump, represent vastly different views of the challenges and opportunities that the country faces, and the role of the United States on the international stage.
Like all elections, the 5 November vote is about much more than science. However, the fate of scientific research, evidence-based lawmaking and the government’s receptiveness to independent science-policy advice will be key determinants of the country’s future course and long-term well-being. And, as we reported in a News Feature on 23 October (Nature 634, 770–774; 2024), US science could be at an inflection point: the election and a range of domestic and global forces could challenge the primacy that the country has held since the Second World War.
A priority for both the winning presidential candidate and the new members of Congress must be ensuring that US science continues to thrive. This is essential if the world is to solve shared challenges, such as the climate crisis, inequality and societal divisions — and that means retaining the openness and collaborative spirit that have characterized US science for much of the past 75 years. US scientists work with peers around the world, which has helped to position the country at the centre of fundamental, applied and translational research, while creating bonds of friendship and collegiality between US researchers and their international collaborators. These bonds are needed now more than ever. The United States needs leaders who fully understand the responsibilities that come with power and, moreover, are wholeheartedly committed to respecting facts or the consensus of evidence while governing.
Harris (…) has broadly sought to advance policies that are in line with the scientific consensus and with the objective of keeping people safe and protecting public health and the environment. The Biden–Harris administration’s signature achievement is the plan to invest more than US$1 trillion in climate and clean-energy technologies over a decade — albeit while overseeing record levels of production of oil and natural gas in the short term. A landmark piece of legislation passed by Congress in 2022, called The Inflation Reduction Act, is a historic investment that seeks to modernize US manufacturing and create jobs in the clean-technology industry. At the same time, the administration has sought to craft and implement plans to insulate regulatory agencies, such as the Environmental Protection Agency (EPA), from political interference (…)
That record is in stark contrast to what happened during Trump’s presidency, from 2017 to 2021. As president, Trump not only repeatedly ignored research-informed knowledge, but also undermined national and global science and public-health agencies. He has denied climate science, lied about the federal government’s response to hurricane forecasts and asked scientists to investigate whether disinfectants could be used to treat people with COVID-19. He pulled the United States out of the World Health Organization in the middle of a once-in-a-century pandemic. He withdrew the country from both the Paris climate agreement and the Joint Comprehensive Plan of Action (also called the Iran nuclear deal) (…) He instilled fear at the EPA, including by rolling back climate policies and making it harder for its research workforce to be able to function independently of politicians (…)
If anything, Trump’s speech has coarsened. In the past few weeks alone, he has falsely claimed that millions of migrants are “pouring into our country from prisons, jails, from mental institutions and insane asylums” and eating people’s pets, and that members of the Democratic Party support the execution of babies after birth. The risks of a second Trump presidency continue to mount. It wouldn’t be easy for a new administration to reverse the investments pledged by the Inflation Reduction Act, but Trump has promised to try. He has said he will ramp up fossil-fuel production and promised to reclassify the positions of tens of thousands of federal employees, including scientists and senior officials in the executive branch of government. That is an alarming development that would require reversing the rule that the Biden administration has crafted to prevent such action. It would undermine a basic premise of modern governance the world over: that scientific and technical specialists working in government are recruited for their expertise, not on the basis of their loyalty to the president or a political party, which is what Trump wants to do.
Political leaders, irrespective of party membership or ideology, generally agree on the need for a society that creates jobs, promotes better health and advances science. But solutions for the world’s mounting problems can come only from a shared, accurate understanding of reality. A lack of regard for the law and evidence fosters mistrust of scientists and institutions of state. That, in turn, weakens the foundations of democracy, both in the United States and around the world. A second Trump presidency would have an even more destabilizing effect globally, giving the green light to yet more leaders like him.
Portland murals [jatp]
Posted in Books, pictures, Running, Statistics, Travel, University life with tags airbnb, American Statistical Association, ASA, homless people, jatp, Joint Statistical Meeting, JSM 2024, murals, Oregon, Pacific North West, Portland, United States of America, Willamette River on September 3, 2024 by xi'an
JSM 2024, Portland, miniday 4
Posted in Books, pictures, Running, Statistics, Travel, University life with tags AI, American Statistical Association, ASA, Bayesian decision theory, Bayesian nonparametrics, Bayesian privacy, BIRS, British Columbia, classification, contextual integrity, data science, differential privacy, draw bridge, ERC, federated learning, generalised Bayesian inference, Joint Statistical Meeting, JSM 2024, Kelowna, Ocean, open water swimming, Oregon, Pacific North West, Portland, Seattle, United States of America, University of Washington, Willamette River on August 11, 2024 by xi'an
Final (half)day at JSM is always a sad thing as most people have left, people are busy dismantling booths and packing boxes, and the few remaining participants are fidgety and sitting on their suitcases (there may have been more suitcases than people in the main area that day!), cafés are minimally staffed or simply closed. Hence not the best time-slot to deliver one’s talk! Still, a few dozen people attended our session. The session topic was Bridge the Gap: Differential Privacy and Statistical Analysis, organised by Bei Jiang whom I met last summer in Kelowna, at a BIRS workshop on privacy. Where I spoke on setting up a complete decision-theoretic framework, as developed (and still in development) within our Ocean group, esp. Joshua Bon, Stan du Ché, and Judith Rousseau. (Rather than on the original plan of talking about convergence versus privacy, as a criticism of differential privacy.) The other talks were by Shurong Li, strongly set with differential privacy when record linkage is present, and Xuan Bi on a fully decentralised federated learning with local exchanges of global gradients that limit privacy leaks. (With a mention of gossip learning I hadn’t seen previously!)

I enjoyed even more the session due to Naisyin Wang giving a discussion on the three talks, in closes the particular because I had not seen her in years, if a few times since she was my teaching assistant in Cornell in a Bayesian decision theory class I was building on the spot (with Linda Zhao as a student!). Which nicely closes the loop given the topic of my talk, of which she was quite supportive! While calling for debiasing post-processing and wondering about a two-dimensional decision theoretic perspective rather than a unidimensional one under hard privacy constraints.

On the way out, after parting from the few friends remaining in the convention centre, I spotted the nearby (steel) bridge being raised, although I could not see the boat responsible for it. I had been unaware of this possibility while running over and under it, as well as swimming thrice under it. And we left Portland in the early afternoon, heading for Seattle and a celebration of Adrian Raftery’s career.
JSM 2024, Portland, Day 3
Posted in pictures, Running, Statistics, Travel, University life with tags AI, American Statistical Association, Arianna Rosenbluth, ASA, bandits, Bayesian lasso, Bayesian model averaging, Bayesian model choice, Bayesian nonparametrics, classification, Committee of Presidents of Statistical Societies, completely random measures, convergence diagnostics, COPSS Presidents' Award, data science, David Blackwell, EM algorithm, generalised Bayesian inference, Gibbs measure, Ising model, jISBA, Joint Statistical Meeting, JSM 2024, missing species problem, Monte Carlo EM, Mount Hood National Forest, open water swimming, Oregon, Portland, Rutgers University, spike-and-slab prior, stochastic localization, Thompson sampling, United States of America, Willamette River on August 9, 2024 by xi'an
Bayesian contributed session as the first round of the third day (with a choice of five parallel sessions featuring Bayesian topics!!, actually easier to pick than among the following eight parallel sessions of the 10:30 schedule!!!), with a talk by Tahir Ekin on adversarial outlier detection that could connect with our Oceaner(c) privacy concerns. Then one involving spike & slab (a theme to figure prominently in this special day!!) in mixed response models by Sameer Deshpande, seeking a (unBayesian!) MAP for a latent variable model by Monte Carlo EM. Followed by a talk by Yunyi Shen on completely random measures for estimating the (distribution of the) number of species in heterogeneous populations. Next, Valentin Zulj on (frequentist rather than) Bayesian stacking, on estimating optimal weights for model averaging (which should be posterior probabilities in a pure Bayesian mindframe), including a score function that could lead to generalised Bayesian inference on said weights. Finishing with a talk by Chaegeun Song on correcting Bayesian credible sets towards (frequentist, again!!!) exact coverage for classification (which reminded me of my very first paper with George on correcting frequentist confidence for Binomial observations). With which I could not really engage as seeking a specific coverage level did not seem relevant, imho, but I appreciated the wheel plot representation.
My second morn session was about modern (what else?!) sampling algorithms, although I spent the first dozen minutes wondering whether or not I had entered the wrong room. Until Tianhao Wang focussed on Thompson sampling for bandits. It did prove far enough from my interest for my (sleep deprived) attention to drift too quickly. Only the talk by Yuchen Wu on a spike & slab (as suits the day!) challenge captured enough this wandering attention. Crossing further into my realm of primary topics by considering a target distribution that is a product of distributions. But I did not get from her presentation how a product measure decomposition was inducing higher efficiency (and did not find answers within the arXived preprint). Unless it exploited specific features of the target, like conditional independence between the components. The last talk was by Brice Huang on sampling low temperature Gibbs measures using stochastic localisation.
After coming upon a row of food trucks across the conference centre and being unfairly attracted by an Ethiopian injera picture into a terrible wrap, I returned for the Skeptical about AI session, just a few minutes late, only to find accessing the session was impossible! Quite sad to miss the presentations and the arguments (even though I had heard a previous talk by Genevera Allen when visiting Rutgers two years ago). As a second best, I then joined the recent (of course!) Advances in Bayesian Computation (aka ABC?!) session with a medley of topics, including a data subset versus data sketching model reduction by Sudipto Saha. Which could have consequences on our privacy strategies. And marginal evidence estimation for the Bayesian Lasso by Christopher Hans while avoiding data completion. And another latent variable model with a sequential variational Bayes approach by Bao Anh Vu, using at one point Cappé et al. (2005) EM-based approximation to the log likelihood gradient. Finishing by a back-to-the-future talk by Luke Duttweiler on MCMC convergence diagnostics. Comparing several chains via proximity maps that themselves require some preliminary knowledge about the MCMC kernel. (Nice title though, “the traceplot thickens”!)
The crux of the day was however the 2024 COPSS Award ceremony with several friends featuring among the recipients, Danielle Durante for the Emerging Leaders Award, Regina Liu for the Elizabeth L. Scott Award and Veronika Rockova for the Presidents’ Award. Congrats!!!



